Last updated on 2023-11-14 09:09:45 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 4.16.0 | 44.67 | 1029.29 | 1073.96 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 4.16.0 | 35.59 | 610.09 | 645.68 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 4.16.0 | 1054.06 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 4.16.0 | 1027.85 | ERROR | |||
| r-devel-windows-x86_64 | 4.16.0 | 36.00 | 841.00 | 877.00 | NOTE | |
| r-patched-linux-x86_64 | 4.16.0 | 67.03 | 1010.29 | 1077.32 | OK | |
| r-release-linux-x86_64 | 4.16.0 | 35.70 | 951.16 | 986.86 | OK | |
| r-release-macos-arm64 | 4.16.0 | 315.00 | NOTE | |||
| r-release-macos-x86_64 | 4.16.0 | 819.00 | NOTE | |||
| r-release-windows-x86_64 | 4.16.0 | 53.00 | 1002.00 | 1055.00 | NOTE | |
| r-oldrel-macos-arm64 | 4.16.0 | 306.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 4.16.0 | 426.00 | NOTE | |||
| r-oldrel-windows-x86_64 | 4.16.0 | 51.00 | 956.00 | 1007.00 | NOTE |
Version: 4.16.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [672s/386s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library("testthat")
> library("umx")
Loading required package: OpenMx
For an overview type '?umx'
Attaching package: 'umx'
The following object is masked from 'package:stats':
loadings
>
> test_check("umx")
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:------|--:|:-----|:----|:-------|--------:|:-----|:------------------|:---------|
|CP3fac | 51| | | | 184511.4|0 | |-2lnL |
|dropC | 42|233.3 |9 |< 0.001 | 184726.7|215.3 |CP3fac |-2lnL |
Table: Common Factor Paths
| | A|C | E|
|:---------------|----:|:--|----:|
|Common.factor.1 | 0.79|. | 0.62|
|Common.factor.2 | 0.65|. | 0.76|
|Common.factor.3 | 0.29|. | 0.96|
Table: Loadings of each trait on the Common Factors
| | CP1| CP2| CP3|
|:---|-----:|-----:|-----:|
|gff | 0.44| 0.34| 0.08|
|fc | 0.98| -0.05| 0.02|
|qol | 0.31| 0.71| 0.10|
|hap | 0.24| 0.52| 0.82|
|sat | 0.27| 0.61| 0.43|
|AD | -0.31| -0.43| -0.23|
Table: Specific-factor loadings
| |gff |fc |qol |hap |sat |AD |
|:----------|:----|:----|:----|:---|:----|:----|
|Specific a |0.45 |. |0.14 |. |0.17 |0.38 |
|Specific c |. |. |. |. |. |. |
|Specific e |0.7 |0.16 |0.61 |. |0.59 |0.73 |
Table: Means (from model$top$expMean)
| | gff_T1| fc_T1| qol_T1| hap_T1| sat_T1| AD_T1| gff_T2| fc_T2| qol_T2| hap_T2| sat_T2| AD_T2|
|:---------|------:|------:|------:|------:|------:|-----:|------:|------:|------:|------:|------:|-----:|
|intercept | 38.39| -13.37| 7.81| 22.97| 27.56| 4.09| 38.39| -13.37| 7.81| 22.97| 27.56| 4.09|
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:------|--:|:-------|:----|:-------|--------:|:-------|:------------------|:---------|
|CP3fac | 51| | | | 184511.4|0 | |-2lnL |
|dropC | 42|233.302 |9 |< 0.001 | 184726.7|215.302 |CP3fac |-2lnL |
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
G_to_x2 0.469 0.503 0.541 0 0
G_to_x3 0.538 0.577 0.619 0 0
G_to_x4 0.657 0.702 0.751 0 0
G_to_x5 0.746 0.795 0.850 0 0
x1_with_x1 0.036 0.041 0.047 0 0
x2_with_x2 0.033 0.038 0.044 0 0
x3_with_x3 0.035 0.041 0.047 0 0
x4_with_x4 0.033 0.039 0.047 0 0
x5_with_x5 0.030 0.036 0.044 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
G_to_x2 0.469 0.503 0.541 0 0
G_to_x3 0.538 0.577 0.619 0 0
G_to_x4 0.657 0.702 0.751 0 0
G_to_x5 0.746 0.795 0.850 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
The hypothesis that 'drop_path_2_x2' was tested by dropping drop_path_2_x2 from 'One Factor'. This caused a significant loss of fit (χ²(1) = 946, p = < 0.001: AIC = -2696.599 change in AIC = 943.998).
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------|--:|:-------|:----|:-------|---------:|:-------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------|--:|:-------|:----|:-------|---------:|:-------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
<table class=" lightable-paper lightable-striped" style='font-family: "Arial Narrow", arial, helvetica, sans-serif; width: auto !important; margin-left: auto; margin-right: auto;'>
<caption>Table of Model Comparisons</caption>
<thead>
<tr>
<th style="text-align:left;"> Model </th>
<th style="text-align:right;"> EP </th>
<th style="text-align:left;"> Δ Fit </th>
<th style="text-align:left;"> Δ df </th>
<th style="text-align:left;"> p </th>
<th style="text-align:right;"> AIC </th>
<th style="text-align:left;"> Δ AIC </th>
<th style="text-align:left;"> Compare with Model </th>
<th style="text-align:left;"> Fit units </th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;"> One Factor </td>
<td style="text-align:right;"> 10 </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> </td>
<td style="text-align:right;"> -3640.597 </td>
<td style="text-align:left;"> 0 </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> -2lnL </td>
</tr>
<tr>
<td style="text-align:left;"> drop_path_2_x2 </td>
<td style="text-align:right;"> 9 </td>
<td style="text-align:left;"> 945.998 </td>
<td style="text-align:left;"> 1 </td>
<td style="text-align:left;"> < 0.001 </td>
<td style="text-align:right;"> -2696.599 </td>
<td style="text-align:left;"> 943.998 </td>
<td style="text-align:left;"> One Factor </td>
<td style="text-align:left;"> -2lnL </td>
</tr>
</tbody>
</table>
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
The 'One Factor' model is the best fitting model according to AIC.AIC weight-based {Wagenmakers, 2004, 192-196} conditional probabilities of being the best model for 'One Factor', 'drop_path_2_x2', and 'drop_path_2_x2_and_3' respectively are: '1', '0', and '0' Using MuMIn::Weights(AIC()).
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
|drop_path_2_x2 | 9| | | | -2696.599|943.998 | |-2lnL |
|drop_path_2_x2 | 9|0 |0 | | -2696.599|943.998 |drop_path_2_x2 |-2lnL |
|drop_path_2_x2_and_3 | 8|993.341 |1 |< 0.001 | -1705.258|1935.339 |drop_path_2_x2 |-2lnL |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:----------|------------:|:------|:-----------------|:---------------|
|11 |G_with_G | 1.00|0 |1 [1, 1] |Factor Variance |
|1 |G_to_x1 | 0.89|0.01 |0.89 [0.87, 0.91] |Factor loading |
|2 |G_to_x2 | 0.93|0.01 |0.93 [0.92, 0.95] |Factor loading |
|3 |G_to_x3 | 0.94|0.01 |0.94 [0.93, 0.95] |Factor loading |
|4 |G_to_x4 | 0.96|0 |0.96 [0.95, 0.97] |Factor loading |
|5 |G_to_x5 | 0.97|0 |0.97 [0.97, 0.98] |Factor loading |
|6 |x1_with_x1 | 0.21|0.02 |0.21 [0.17, 0.24] |Residual |
|7 |x2_with_x2 | 0.13|0.01 |0.13 [0.11, 0.15] |Residual |
|8 |x3_with_x3 | 0.11|0.01 |0.11 [0.09, 0.13] |Residual |
|9 |x4_with_x4 | 0.07|0.01 |0.07 [0.06, 0.09] |Residual |
|10 |x5_with_x5 | 0.05|0.01 |0.05 [0.04, 0.07] |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:----------|------------:|:------|:-----------------|:---------------|
|11 |G_with_G | 1.00|0 |1 [1, 1] |Factor Variance |
|1 |G_to_x1 | 0.89|0.01 |0.89 [0.87, 0.91] |Factor loading |
|2 |G_to_x2 | 0.93|0.01 |0.93 [0.92, 0.95] |Factor loading |
|3 |G_to_x3 | 0.94|0.01 |0.94 [0.93, 0.95] |Factor loading |
|4 |G_to_x4 | 0.96|0 |0.96 [0.95, 0.97] |Factor loading |
|5 |G_to_x5 | 0.97|0 |0.97 [0.97, 0.98] |Factor loading |
|6 |x1_with_x1 | 0.21|0.02 |0.21 [0.17, 0.24] |Residual |
|7 |x2_with_x2 | 0.13|0.01 |0.13 [0.11, 0.15] |Residual |
|8 |x3_with_x3 | 0.11|0.01 |0.11 [0.09, 0.13] |Residual |
|9 |x4_with_x4 | 0.07|0.01 |0.07 [0.06, 0.09] |Residual |
|10 |x5_with_x5 | 0.05|0.01 |0.05 [0.04, 0.07] |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Estimate|SE |type |
|:--|:----------|--------:|:----|:---------------|
|11 |G_with_G | 1.00|0 |Factor Variance |
|1 |G_to_x1 | 0.40|0.02 |Factor loading |
|2 |G_to_x2 | 0.50|0.02 |Factor loading |
|3 |G_to_x3 | 0.58|0.02 |Factor loading |
|4 |G_to_x4 | 0.70|0.02 |Factor loading |
|5 |G_to_x5 | 0.80|0.03 |Factor loading |
|6 |x1_with_x1 | 0.04|0 |Residual |
|7 |x2_with_x2 | 0.04|0 |Residual |
|8 |x3_with_x3 | 0.04|0 |Residual |
|9 |x4_with_x4 | 0.04|0 |Residual |
|10 |x5_with_x5 | 0.04|0 |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate| Std.SE|CI |type |
|:--|:---------|------------:|------:|:-------------------|:----|
|12 |one_to_x1 | -0.02| 0.1|-0.02 [-0.22, 0.18] |Mean |
|13 |one_to_x2 | -0.10| 0.1|-0.1 [-0.3, 0.1] |Mean |
|14 |one_to_x3 | -0.08| 0.1|-0.08 [-0.28, 0.11] |Mean |
|15 |one_to_x4 | -0.07| 0.1|-0.07 [-0.27, 0.12] |Mean |
|16 |one_to_x5 | -0.07| 0.1|-0.07 [-0.26, 0.13] |Mean |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
Table: General Independent Pathway path loadings
| | ai1| ci1| ei1|
|:---|-----:|-----:|-----:|
|hap | 0.47| -0.24| 0.77|
|sat | 0.51| -0.20| 0.56|
|AD | -0.54| 0.06| -0.27|
Table: Specific factor loadings
| |hap |sat |AD |
|:----------|:----|:----|:----|
|Specific a |0.14 |0.3 |0.45 |
|Specific c |. |. |. |
|Specific e |0.32 |0.54 |0.65 |
Table: Means (from model$top$expMean)
| | hap_T1| sat_T1| AD_T1| hap_T2| sat_T2| AD_T2|
|:---------|------:|------:|-----:|------:|------:|-----:|
|intercept | 22.98| 27.56| 4.14| 22.98| 27.56| 4.14|
Table: Parameter loadings for model 'tim'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:------------------|------------:|:------|:--------------------|:-------------|
|5 |litres_with_wt | 0.89|0.04 |0.89 [0.81, 0.96] |Manifest Cov |
|1 |wt_to_mpg | -0.54|0.17 |-0.54 [-0.89, -0.2] |Manifest path |
|2 |litres_to_mpg | -0.36|0.18 |-0.36 [-0.71, -0.02] |Manifest path |
|7 |one_to_mpg | 5.89|0.68 |5.89 [4.56, 7.22] |Mean |
|8 |one_to_wt | 3.34|0.45 |3.34 [2.45, 4.23] |Mean |
|9 |one_to_litres | 1.89|0.3 |1.89 [1.31, 2.47] |Mean |
|3 |mpg_with_mpg | 0.22|0.07 |0.22 [0.08, 0.35] |Residual |
|4 |wt_with_wt | 1.00|0 |1 [1, 1] |Residual |
|6 |litres_with_litres | 1.00|0 |1 [1, 1] |Residual |
Table: Raw parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1| c1| e1|
|:--|----:|---:|----:|
|ht | 0.61| 0.1| 0.24|
Table: Means (from model$top$expMean)
| | ht1| ht2|
|:---------|------:|------:|
|intercept | 16.252| 16.252|
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:-----|--:|:------|:----|:--|--------:|:------|:------------------|:---------|
|ADE | 4| | | | 5987.341|0 | |-2lnL |
|ACE | 4|-0.139 |0 | | 5987.202|-0.139 |ADE |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:-----|--:|:-----|:----|:--|-------:|:-----|:------------------|:---------|
|ACE | 4| | | | 5987.20|0 | |-2lnL |
|ADE | 4|0.14 |0 | | 5987.34|0.14 |ACE |-2lnL |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; D: dominance effects; E: unique environment.
| | a1|d1 | e1|
|:--|----:|:--|----:|
|ht | 0.93|. | 0.36|
Table: Means (from model$top$expMean)
| | ht1| ht2|
|:---------|------:|------:|
|intercept | 16.252| 16.252|
(Intercept) B = 60.201 [59.505, 60.898], t = 169.359, p < 0.001
age B = 0.106 [0.088, 0.125], t = 11.183, p < 0.001
R² = 0.017 (adj = 0.016)(Intercept) B = 1.711 [1.705, 1.717], t = 590.26, p < 0.001
age B = -0.001 [-0.001, -0.001], t = -12.358, p < 0.001
R² = 0.02 (adj = 0.02)
Table: Standardized parameter estimates from a 2-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|a2 | c1|c2 | e1|e2 |
|:--|----:|:----|-----:|:--|----:|:---|
|ht | 0.76| | 0.43| | 0.49| |
|wt | 0.60|0.68 | -0.10|. | 0.02|0.4 |
Table: Means (from model$top$expMean)
| | ht1| wt1| ht2| wt2|
|:---------|-----:|------:|-----:|------:|
|intercept | -0.39| -0.532| -0.39| -0.532|
'data.frame': 80 obs. of 18 variables:
$ fam : int 1 2 3 4 5 6 7 8 9 10 ...
$ age : int 21 24 21 21 19 26 23 29 24 28 ...
$ zyg : int 1 1 1 1 1 1 1 1 1 1 ...
$ part : int 2 2 2 2 2 2 2 2 2 2 ...
$ wt1 : num -0.502 -0.844 -0.758 0.181 -1.185 ...
$ wt2 : num -0.588 -0.929 -1.185 1.035 -1.356 ...
$ ht1 : num 1.7 1.63 1.65 1.57 1.61 ...
$ ht2 : num 1.7 1.63 1.68 1.65 1.63 ...
$ htwt1 : num 20.1 20.3 20.2 26.8 19.3 ...
$ htwt2 : num 19.7 19.9 17.7 27.9 18.1 ...
$ bmi1 : num 21 21.1 21 23 20.7 ...
$ bmi2 : num 20.9 21 20.1 23.3 20.3 ...
$ cohort : chr "younger" "younger" "younger" "younger" ...
$ zygosity: Factor w/ 5 levels "MZFF","MZMM",..: 1 1 1 1 1 1 1 1 1 1 ...
$ age1 : int 21 24 21 21 19 26 23 29 24 28 ...
$ age2 : int 21 24 21 21 19 26 23 29 24 28 ...
$ obese1 : Ord.factor w/ 3 levels "normal"<"overweight"<..: 2 2 2 3 1 3 2 1 1 3 ...
$ obese2 : Ord.factor w/ 3 levels "normal"<"overweight"<..: 1 1 1 3 1 3 2 1 1 2 ...
Table: Standardized parameter estimates from a 2-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|a2 | c1|c2 | e1|e2 |
|:-----|----:|:----|----:|:--|----:|:----|
|wt | 0.87| | 0.06| | 0.48| |
|obese | 0.63|0.52 | 0.25|. | 0.40|0.33 |
Table: Means (from model$top$expMean)
| | wt1|obese1 | wt2|obese2 |
|:---------|------:|:------|------:|:------|
|intercept | -0.414|0 | -0.414|0 |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:--|----:|:--|----:|
|wt | 0.87|. | 0.49|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.698| 21.698|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.45|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.305| 21.305|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.45|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.313| 21.313|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.46|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.32| 21.32|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.46|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.329| 21.329|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.47|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.34| 21.34|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.47|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.351| 21.351|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.48|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.364| 21.364|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.48|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.378| 21.378|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.394| 21.394|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.411| 21.411|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.429| 21.429|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.449| 21.449|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.47| 21.47|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.492| 21.492|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.514| 21.514|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.536| 21.536|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.558| 21.558|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.58| 21.58|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.601| 21.601|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.621| 21.621|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.641| 21.641|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.66| 21.66|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.679| 21.679|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.698| 21.698|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.718| 21.718|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.739| 21.739|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|----:|
|bmi |. | 0.8| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.763| 21.763|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.788| 21.788|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.816| 21.816|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.847| 21.847|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.88| 21.88|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|----:|
|bmi |. | 0.8| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.914| 21.914|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.949| 21.949|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.985| 21.985|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.019| 22.019|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.051| 22.051|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.081| 22.081|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.108| 22.108|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.131| 22.131|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.152| 22.152|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 22.17| 22.17|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.185| 22.185|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.197| 22.197|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.208| 22.208|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.216| 22.216|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.223| 22.223|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.229| 22.229|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.233| 22.233|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.238| 22.238|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.242| 22.242|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.86| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.246| 22.246|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.251| 22.251|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.256| 22.256|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.261| 22.261|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.266| 22.266|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 22.27| 22.27|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.272| 22.272|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.272| 22.272|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.268| 22.268|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.259| 22.259|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.244| 22.244|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.223| 22.223|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.194| 22.194|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.158| 22.158|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.115| 22.115|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.78| 0.62|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.066| 22.066|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.76| 0.66|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.015| 22.015|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.72| 0.69|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.961| 21.961|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.68| 0.73|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.909| 21.909|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.63| 0.77|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.859| 21.859|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.58| 0.81|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.814| 21.814|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.53| 0.85|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.776| 21.776|
polite note: in future, please use report = 'markdown', not file='markdown'. file is for choosing a custom html file when writing to the browser with report= 'html'
Table: Standardized parameter estimates from a 1-factor Direct variance ACE model. A: additive genetic; C: common environment; E: unique environment.
| | A1| C1| E1|
|:---|-----:|------:|-----:|
|bmi | 0.807| -0.063| 0.256|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.649| 21.649|
Table: Parameter loadings for model 'check_model_ex'
| |name | Estimate|SE |type |
|:--|:----------|--------:|:----|:---------------|
|11 |G_with_G | 1.00|0 |Factor Variance |
|1 |G_to_x1 | 0.89|0.02 |Factor loading |
|2 |G_to_x2 | 0.93|0.02 |Factor loading |
|3 |G_to_x3 | 0.94|0.02 |Factor loading |
|4 |G_to_x4 | 0.96|0.02 |Factor loading |
|5 |G_to_x5 | 0.97|0.03 |Factor loading |
|6 |x1_with_x1 | 0.21|0 |Residual |
|7 |x2_with_x2 | 0.13|0 |Residual |
|8 |x3_with_x3 | 0.11|0 |Residual |
|9 |x4_with_x4 | 0.07|0 |Residual |
|10 |x5_with_x5 | 0.05|0 |Residual |
[1] "cyl"
[1] "cylinder"
(Intercept) B = 34.661 [29.452, 39.87], t = 13.609, p < 0.001
cyl B = -1.587 [-3.043, -0.131], t = -2.23, p = 0.034
disp B = -0.021 [-0.042, 0], t = -2.007, p = 0.054
R² = 0.76 (adj = 0.743)(Intercept) B = 53.445 [31.077, 75.814], t = 4.894, p < 0.001
cyl B = -8.367 [-16.359, -0.376], t = -2.145, p = 0.041
I(cyl^2) B = 0.597 [-0.096, 1.291], t = 1.766, p = 0.088
disp B = -0.027 [-0.049, -0.006], t = -2.574, p = 0.016
R² = 0.784 (adj = 0.76)(Intercept) B = 34.661 [31.149, 38.173], t = 19.737, p < 0.001
cyl B = -1.587 [-2.569, -0.606], t = -3.234, p = 0.002
disp B = -0.021 [-0.035, -0.006], t = -2.91, p = 0.005
R² = 0.76 (adj = 0.752)(Intercept) B = 34.661 [29.452, 39.87], t = 13.609, p < 0.001
cyl B = -1.587 [-3.043, -0.131], t = -2.23, p = 0.034
disp B = -0.021 [-0.042, 0], t = -2.007, p = 0.054
R² = 0.76 (adj = 0.743)(Intercept) B = -32.432 [-98.452, 33.589], t = -1.005, p = 0.323
cyl B = 24.515 [6.063, 42.966], t = 2.717, p = 0.011
disp B = 0.119 [-0.147, 0.385], t = 0.915, p = 0.368
R² = 0.702 (adj = 0.681)[ FAIL 1 | WARN 7 | SKIP 27 | PASS 339 ]
══ Skipped tests (27) ══════════════════════════════════════════════════════════
• empty test (27): 'test_poly.r:6:1', 'test_umxBuild_run_modify.r:94:1',
'test_umxBuild_run_modify.r:131:1', 'test_umxBuild_run_modify.r:150:1',
'test_umxBuild_run_modify.r:195:1', 'test_umxCP.r:4:1',
'test_umxFactorScores.r:9:1', 'test_umxFitAndReporting.r:191:1',
'test_umxFitAndReporting.r:205:1', 'test_umxMatrixFree.R:6:1',
'test_umxPath.r:7:1', 'test_umx_ACE_etc.r:6:1', 'test_umx_ACE_etc.r:26:1',
'test_umx_ACE_etc.r:69:2', 'test_umx_ACE_etc.r:118:2',
'test_umx_ACE_etc.r:135:2', 'test_umx_ACE_etc.r:163:2',
'test_umx_ACE_etc.r:185:2', 'test_umx_ACE_etc.r:222:1',
'test_umx_ACE_etc.r:236:1', 'test_umx_ACE_etc.r:248:1',
'test_umx_CLPM.r:6:1', 'test_umx_DOC_etc.r:6:1', 'test_umx_misc.r:54:1',
'test_umx_misc.r:96:1', 'test_umx_misc.r:111:1', 'test_umx_misc.r:161:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_umxPower.r:36:2'): umxPower works ──────────────────────────────
Error in `grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y,
resolveHJust(x$just, x$hjust), resolveVJust(x$just, x$vjust),
x$rot, as.numeric(NA))`: conversion failure on 'Power = 1 - β' in 'mbcsToSbcs': for β
Backtrace:
▆
1. ├─umx::umxPower(m1, "X_with_Y", explore = TRUE) at test_umxPower.r:36:9
2. │ ├─base::print(p)
3. │ ├─base::print(p)
4. │ └─ggplot2:::print.ggplot(p)
5. │ ├─grid::grid.draw(gtable)
6. │ └─grid:::grid.draw.gTree(gtable)
7. │ └─grDevices::recordGraphics(drawGTree(x), list(x = x), getNamespace("grid"))
8. ├─grid:::drawGTree(x)
9. │ ├─grid:::preDraw(x)
10. │ └─grid:::preDraw.gTree(x)
11. │ └─grid:::pushvpgp(x)
12. │ ├─grid:::pushgrobvp(x$vp)
13. │ └─grid:::pushgrobvp.viewport(x$vp)
14. │ └─grid::pushViewport(vp, recording = FALSE)
15. │ └─base::lapply(vps, push.vp, recording)
16. │ ├─grid (local) FUN(X[[i]], ...)
17. │ └─grid:::push.vp.viewport(X[[i]], ...)
18. │ └─grid:::grid.Call.graphics(C_setviewport, vp, TRUE)
19. ├─grid (local) `<fn>`(`<titleGrb>`)
20. ├─grid:::preDraw.gTree(`<titleGrb>`)
21. │ └─grid:::pushvpgp(x)
22. │ ├─grid:::pushgrobvp(x$vp)
23. │ └─grid:::pushgrobvp.viewport(x$vp)
24. │ └─grid::pushViewport(vp, recording = FALSE)
25. │ └─base::lapply(vps, push.vp, recording)
26. │ ├─grid (local) FUN(X[[i]], ...)
27. │ └─grid:::push.vp.vpTree(X[[i]], ...)
28. │ ├─grid:::push.vp(vp$parent, recording)
29. │ └─grid:::push.vp.viewport(vp$parent, recording)
30. │ └─grid:::grid.Call.graphics(C_setviewport, vp, TRUE)
31. └─grid (local) `<fn>`(`<text>`)
32. ├─grid::widthDetails(x)
33. └─grid:::widthDetails.text(x)
34. └─grid:::grid.Call(...)
[ FAIL 1 | WARN 7 | SKIP 27 | PASS 339 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 4.16.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [356s/409s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library("testthat")
> library("umx")
Loading required package: OpenMx
For an overview type '?umx'
Attaching package: 'umx'
The following object is masked from 'package:stats':
loadings
>
> test_check("umx")
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:------|--:|:-----|:----|:-------|--------:|:-----|:------------------|:---------|
|CP3fac | 51| | | | 184511.4|0 | |-2lnL |
|dropC | 42|233.3 |9 |< 0.001 | 184726.7|215.3 |CP3fac |-2lnL |
Table: Common Factor Paths
| | A|C | E|
|:---------------|----:|:--|----:|
|Common.factor.1 | 0.79|. | 0.62|
|Common.factor.2 | 0.65|. | 0.76|
|Common.factor.3 | 0.29|. | 0.96|
Table: Loadings of each trait on the Common Factors
| | CP1| CP2| CP3|
|:---|-----:|-----:|-----:|
|gff | 0.44| 0.34| 0.08|
|fc | 0.98| -0.05| 0.02|
|qol | 0.31| 0.71| 0.10|
|hap | 0.24| 0.52| 0.82|
|sat | 0.27| 0.61| 0.43|
|AD | -0.31| -0.43| -0.23|
Table: Specific-factor loadings
| |gff |fc |qol |hap |sat |AD |
|:----------|:----|:----|:----|:---|:----|:----|
|Specific a |0.45 |. |0.14 |. |0.17 |0.38 |
|Specific c |. |. |. |. |. |. |
|Specific e |0.7 |0.16 |0.61 |. |0.59 |0.73 |
Table: Means (from model$top$expMean)
| | gff_T1| fc_T1| qol_T1| hap_T1| sat_T1| AD_T1| gff_T2| fc_T2| qol_T2| hap_T2| sat_T2| AD_T2|
|:---------|------:|------:|------:|------:|------:|-----:|------:|------:|------:|------:|------:|-----:|
|intercept | 38.39| -13.37| 7.81| 22.97| 27.56| 4.09| 38.39| -13.37| 7.81| 22.97| 27.56| 4.09|
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:------|--:|:-------|:----|:-------|--------:|:-------|:------------------|:---------|
|CP3fac | 51| | | | 184511.4|0 | |-2lnL |
|dropC | 42|233.302 |9 |< 0.001 | 184726.7|215.302 |CP3fac |-2lnL |
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
G_to_x2 0.469 0.503 0.541 0 0
G_to_x3 0.538 0.577 0.619 0 0
G_to_x4 0.657 0.702 0.751 0 0
G_to_x5 0.746 0.795 0.850 0 0
x1_with_x1 0.036 0.041 0.047 0 0
x2_with_x2 0.033 0.038 0.044 0 0
x3_with_x3 0.035 0.041 0.047 0 0
x4_with_x4 0.033 0.039 0.047 0 0
x5_with_x5 0.030 0.036 0.044 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
G_to_x2 0.469 0.503 0.541 0 0
G_to_x3 0.538 0.577 0.619 0 0
G_to_x4 0.657 0.702 0.751 0 0
G_to_x5 0.746 0.795 0.850 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
The hypothesis that 'drop_path_2_x2' was tested by dropping drop_path_2_x2 from 'One Factor'. This caused a significant loss of fit (χ²(1) = 946, p = < 0.001: AIC = -2696.599 change in AIC = 943.998).
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------|--:|:-------|:----|:-------|---------:|:-------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------|--:|:-------|:----|:-------|---------:|:-------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
<table class=" lightable-paper lightable-striped" style='font-family: "Arial Narrow", arial, helvetica, sans-serif; width: auto !important; margin-left: auto; margin-right: auto;'>
<caption>Table of Model Comparisons</caption>
<thead>
<tr>
<th style="text-align:left;"> Model </th>
<th style="text-align:right;"> EP </th>
<th style="text-align:left;"> Δ Fit </th>
<th style="text-align:left;"> Δ df </th>
<th style="text-align:left;"> p </th>
<th style="text-align:right;"> AIC </th>
<th style="text-align:left;"> Δ AIC </th>
<th style="text-align:left;"> Compare with Model </th>
<th style="text-align:left;"> Fit units </th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;"> One Factor </td>
<td style="text-align:right;"> 10 </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> </td>
<td style="text-align:right;"> -3640.597 </td>
<td style="text-align:left;"> 0 </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> -2lnL </td>
</tr>
<tr>
<td style="text-align:left;"> drop_path_2_x2 </td>
<td style="text-align:right;"> 9 </td>
<td style="text-align:left;"> 945.998 </td>
<td style="text-align:left;"> 1 </td>
<td style="text-align:left;"> < 0.001 </td>
<td style="text-align:right;"> -2696.599 </td>
<td style="text-align:left;"> 943.998 </td>
<td style="text-align:left;"> One Factor </td>
<td style="text-align:left;"> -2lnL </td>
</tr>
</tbody>
</table>
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
The 'One Factor' model is the best fitting model according to AIC.AIC weight-based {Wagenmakers, 2004, 192-196} conditional probabilities of being the best model for 'One Factor', 'drop_path_2_x2', and 'drop_path_2_x2_and_3' respectively are: '1', '0', and '0' Using MuMIn::Weights(AIC()).
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
|drop_path_2_x2 | 9| | | | -2696.599|943.998 | |-2lnL |
|drop_path_2_x2 | 9|0 |0 | | -2696.599|943.998 |drop_path_2_x2 |-2lnL |
|drop_path_2_x2_and_3 | 8|993.341 |1 |< 0.001 | -1705.258|1935.339 |drop_path_2_x2 |-2lnL |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:----------|------------:|:------|:-----------------|:---------------|
|11 |G_with_G | 1.00|0 |1 [1, 1] |Factor Variance |
|1 |G_to_x1 | 0.89|0.01 |0.89 [0.87, 0.91] |Factor loading |
|2 |G_to_x2 | 0.93|0.01 |0.93 [0.92, 0.95] |Factor loading |
|3 |G_to_x3 | 0.94|0.01 |0.94 [0.93, 0.95] |Factor loading |
|4 |G_to_x4 | 0.96|0 |0.96 [0.95, 0.97] |Factor loading |
|5 |G_to_x5 | 0.97|0 |0.97 [0.97, 0.98] |Factor loading |
|6 |x1_with_x1 | 0.21|0.02 |0.21 [0.17, 0.24] |Residual |
|7 |x2_with_x2 | 0.13|0.01 |0.13 [0.11, 0.15] |Residual |
|8 |x3_with_x3 | 0.11|0.01 |0.11 [0.09, 0.13] |Residual |
|9 |x4_with_x4 | 0.07|0.01 |0.07 [0.06, 0.09] |Residual |
|10 |x5_with_x5 | 0.05|0.01 |0.05 [0.04, 0.07] |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:----------|------------:|:------|:-----------------|:---------------|
|11 |G_with_G | 1.00|0 |1 [1, 1] |Factor Variance |
|1 |G_to_x1 | 0.89|0.01 |0.89 [0.87, 0.91] |Factor loading |
|2 |G_to_x2 | 0.93|0.01 |0.93 [0.92, 0.95] |Factor loading |
|3 |G_to_x3 | 0.94|0.01 |0.94 [0.93, 0.95] |Factor loading |
|4 |G_to_x4 | 0.96|0 |0.96 [0.95, 0.97] |Factor loading |
|5 |G_to_x5 | 0.97|0 |0.97 [0.97, 0.98] |Factor loading |
|6 |x1_with_x1 | 0.21|0.02 |0.21 [0.17, 0.24] |Residual |
|7 |x2_with_x2 | 0.13|0.01 |0.13 [0.11, 0.15] |Residual |
|8 |x3_with_x3 | 0.11|0.01 |0.11 [0.09, 0.13] |Residual |
|9 |x4_with_x4 | 0.07|0.01 |0.07 [0.06, 0.09] |Residual |
|10 |x5_with_x5 | 0.05|0.01 |0.05 [0.04, 0.07] |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Estimate|SE |type |
|:--|:----------|--------:|:----|:---------------|
|11 |G_with_G | 1.00|0 |Factor Variance |
|1 |G_to_x1 | 0.40|0.02 |Factor loading |
|2 |G_to_x2 | 0.50|0.02 |Factor loading |
|3 |G_to_x3 | 0.58|0.02 |Factor loading |
|4 |G_to_x4 | 0.70|0.02 |Factor loading |
|5 |G_to_x5 | 0.80|0.03 |Factor loading |
|6 |x1_with_x1 | 0.04|0 |Residual |
|7 |x2_with_x2 | 0.04|0 |Residual |
|8 |x3_with_x3 | 0.04|0 |Residual |
|9 |x4_with_x4 | 0.04|0 |Residual |
|10 |x5_with_x5 | 0.04|0 |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate| Std.SE|CI |type |
|:--|:---------|------------:|------:|:-------------------|:----|
|12 |one_to_x1 | -0.02| 0.1|-0.02 [-0.22, 0.18] |Mean |
|13 |one_to_x2 | -0.10| 0.1|-0.1 [-0.3, 0.1] |Mean |
|14 |one_to_x3 | -0.08| 0.1|-0.08 [-0.28, 0.11] |Mean |
|15 |one_to_x4 | -0.07| 0.1|-0.07 [-0.27, 0.12] |Mean |
|16 |one_to_x5 | -0.07| 0.1|-0.07 [-0.26, 0.13] |Mean |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |-0.82 |0.1 |
|c_r1c1 |0.07 |0.23 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |-0.82 |0.1 |
|c_r1c1 |0.07 |0.23 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |-0.82 |0.1 |
|c_r1c1 |0.07 |0.23 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |-0.82 |0.1 |
|c_r1c1 |0.07 |0.23 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |-0.82 |0.1 |
|c_r1c1 |0.07 |0.23 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
Table: General Independent Pathway path loadings
| | ai1| ci1| ei1|
|:---|-----:|-----:|-----:|
|hap | 0.47| 0.24| 0.77|
|sat | 0.51| 0.20| 0.56|
|AD | -0.54| -0.06| -0.27|
Table: Specific factor loadings
| |hap |sat |AD |
|:----------|:----|:----|:----|
|Specific a |0.14 |0.3 |0.45 |
|Specific c |. |. |. |
|Specific e |0.32 |0.54 |0.65 |
Table: Means (from model$top$expMean)
| | hap_T1| sat_T1| AD_T1| hap_T2| sat_T2| AD_T2|
|:---------|------:|------:|-----:|------:|------:|-----:|
|intercept | 22.98| 27.56| 4.14| 22.98| 27.56| 4.14|
Table: Parameter loadings for model 'tim'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:------------------|------------:|:------|:--------------------|:-------------|
|5 |litres_with_wt | 0.89|0.04 |0.89 [0.81, 0.96] |Manifest Cov |
|1 |wt_to_mpg | -0.54|0.17 |-0.54 [-0.89, -0.2] |Manifest path |
|2 |litres_to_mpg | -0.36|0.18 |-0.36 [-0.71, -0.02] |Manifest path |
|7 |one_to_mpg | 5.89|0.68 |5.89 [4.56, 7.22] |Mean |
|8 |one_to_wt | 3.34|0.45 |3.34 [2.45, 4.23] |Mean |
|9 |one_to_litres | 1.89|0.3 |1.89 [1.31, 2.47] |Mean |
|3 |mpg_with_mpg | 0.22|0.07 |0.22 [0.08, 0.35] |Residual |
|4 |wt_with_wt | 1.00|0 |1 [1, 1] |Residual |
|6 |litres_with_litres | 1.00|0 |1 [1, 1] |Residual |
Table: Raw parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1| c1| e1|
|:--|----:|---:|----:|
|ht | 0.61| 0.1| 0.24|
Table: Means (from model$top$expMean)
| | ht1| ht2|
|:---------|------:|------:|
|intercept | 16.252| 16.252|
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:-----|--:|:------|:----|:--|--------:|:------|:------------------|:---------|
|ADE | 4| | | | 5987.341|0 | |-2lnL |
|ACE | 4|-0.139 |0 | | 5987.202|-0.139 |ADE |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:-----|--:|:-----|:----|:--|-------:|:-----|:------------------|:---------|
|ACE | 4| | | | 5987.20|0 | |-2lnL |
|ADE | 4|0.14 |0 | | 5987.34|0.14 |ACE |-2lnL |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; D: dominance effects; E: unique environment.
| | a1|d1 | e1|
|:--|----:|:--|----:|
|ht | 0.93|. | 0.36|
Table: Means (from model$top$expMean)
| | ht1| ht2|
|:---------|------:|------:|
|intercept | 16.252| 16.252|
(Intercept) B = 60.201 [59.505, 60.898], t = 169.359, p < 0.001
age B = 0.106 [0.088, 0.125], t = 11.183, p < 0.001
R² = 0.017 (adj = 0.016)(Intercept) B = 1.711 [1.705, 1.717], t = 590.26, p < 0.001
age B = -0.001 [-0.001, -0.001], t = -12.358, p < 0.001
R² = 0.02 (adj = 0.02)
Table: Standardized parameter estimates from a 2-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|a2 | c1|c2 | e1|e2 |
|:--|----:|:----|-----:|:--|----:|:---|
|ht | 0.76| | 0.43| | 0.49| |
|wt | 0.60|0.68 | -0.10|. | 0.02|0.4 |
Table: Means (from model$top$expMean)
| | ht1| wt1| ht2| wt2|
|:---------|-----:|------:|-----:|------:|
|intercept | -0.39| -0.532| -0.39| -0.532|
'data.frame': 80 obs. of 18 variables:
$ fam : int 1 2 3 4 5 6 7 8 9 10 ...
$ age : int 21 24 21 21 19 26 23 29 24 28 ...
$ zyg : int 1 1 1 1 1 1 1 1 1 1 ...
$ part : int 2 2 2 2 2 2 2 2 2 2 ...
$ wt1 : num -0.502 -0.844 -0.758 0.181 -1.185 ...
$ wt2 : num -0.588 -0.929 -1.185 1.035 -1.356 ...
$ ht1 : num 1.7 1.63 1.65 1.57 1.61 ...
$ ht2 : num 1.7 1.63 1.68 1.65 1.63 ...
$ htwt1 : num 20.1 20.3 20.2 26.8 19.3 ...
$ htwt2 : num 19.7 19.9 17.7 27.9 18.1 ...
$ bmi1 : num 21 21.1 21 23 20.7 ...
$ bmi2 : num 20.9 21 20.1 23.3 20.3 ...
$ cohort : chr "younger" "younger" "younger" "younger" ...
$ zygosity: Factor w/ 5 levels "MZFF","MZMM",..: 1 1 1 1 1 1 1 1 1 1 ...
$ age1 : int 21 24 21 21 19 26 23 29 24 28 ...
$ age2 : int 21 24 21 21 19 26 23 29 24 28 ...
$ obese1 : Ord.factor w/ 3 levels "normal"<"overweight"<..: 2 2 2 3 1 3 2 1 1 3 ...
$ obese2 : Ord.factor w/ 3 levels "normal"<"overweight"<..: 1 1 1 3 1 3 2 1 1 2 ...
Table: Standardized parameter estimates from a 2-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|a2 | c1|c2 | e1|e2 |
|:-----|----:|:----|----:|:--|----:|:----|
|wt | 0.87| | 0.06| | 0.48| |
|obese | 0.63|0.52 | 0.25|. | 0.40|0.33 |
Table: Means (from model$top$expMean)
| | wt1|obese1 | wt2|obese2 |
|:---------|------:|:------|------:|:------|
|intercept | -0.414|0 | -0.414|0 |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:--|----:|:--|----:|
|wt | 0.87|. | 0.49|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.698| 21.698|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.45|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.305| 21.305|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.45|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.313| 21.313|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.46|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.32| 21.32|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.46|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.329| 21.329|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.47|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.34| 21.34|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.47|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.351| 21.351|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.48|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.364| 21.364|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.48|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.378| 21.378|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.394| 21.394|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.411| 21.411|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.429| 21.429|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.449| 21.449|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.47| 21.47|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.492| 21.492|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.514| 21.514|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.536| 21.536|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.558| 21.558|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.58| 21.58|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.601| 21.601|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.621| 21.621|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.641| 21.641|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.66| 21.66|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.679| 21.679|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.698| 21.698|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.718| 21.718|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.739| 21.739|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|----:|
|bmi |. | 0.8| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.763| 21.763|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.788| 21.788|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.816| 21.816|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.847| 21.847|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.88| 21.88|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|----:|
|bmi |. | 0.8| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.914| 21.914|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.949| 21.949|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.985| 21.985|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.019| 22.019|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.051| 22.051|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.081| 22.081|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.108| 22.108|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.131| 22.131|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.152| 22.152|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 22.17| 22.17|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.185| 22.185|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.197| 22.197|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.208| 22.208|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.216| 22.216|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.223| 22.223|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.229| 22.229|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.233| 22.233|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.238| 22.238|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.242| 22.242|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.86| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.246| 22.246|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.251| 22.251|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.256| 22.256|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.261| 22.261|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.266| 22.266|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 22.27| 22.27|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.272| 22.272|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.272| 22.272|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.268| 22.268|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.259| 22.259|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.244| 22.244|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.223| 22.223|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.194| 22.194|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.158| 22.158|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.115| 22.115|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.78| 0.62|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.066| 22.066|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.76| 0.66|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.015| 22.015|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.72| 0.69|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.961| 21.961|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.68| 0.73|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.909| 21.909|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.63| 0.77|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.859| 21.859|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.58| 0.81|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.814| 21.814|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.53| 0.85|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.776| 21.776|
polite note: in future, please use report = 'markdown', not file='markdown'. file is for choosing a custom html file when writing to the browser with report= 'html'
Table: Standardized parameter estimates from a 1-factor Direct variance ACE model. A: additive genetic; C: common environment; E: unique environment.
| | A1| C1| E1|
|:---|-----:|------:|-----:|
|bmi | 0.807| -0.063| 0.256|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.649| 21.649|
Table: Parameter loadings for model 'check_model_ex'
| |name | Estimate|SE |type |
|:--|:----------|--------:|:----|:---------------|
|11 |G_with_G | 1.00|0 |Factor Variance |
|1 |G_to_x1 | 0.89|0.02 |Factor loading |
|2 |G_to_x2 | 0.93|0.02 |Factor loading |
|3 |G_to_x3 | 0.94|0.02 |Factor loading |
|4 |G_to_x4 | 0.96|0.02 |Factor loading |
|5 |G_to_x5 | 0.97|0.03 |Factor loading |
|6 |x1_with_x1 | 0.21|0 |Residual |
|7 |x2_with_x2 | 0.13|0 |Residual |
|8 |x3_with_x3 | 0.11|0 |Residual |
|9 |x4_with_x4 | 0.07|0 |Residual |
|10 |x5_with_x5 | 0.05|0 |Residual |
[1] "cyl"
[1] "cylinder"
(Intercept) B = 34.661 [29.452, 39.87], t = 13.609, p < 0.001
cyl B = -1.587 [-3.043, -0.131], t = -2.23, p = 0.034
disp B = -0.021 [-0.042, 0], t = -2.007, p = 0.054
R² = 0.76 (adj = 0.743)(Intercept) B = 53.445 [31.077, 75.814], t = 4.894, p < 0.001
cyl B = -8.367 [-16.359, -0.376], t = -2.145, p = 0.041
I(cyl^2) B = 0.597 [-0.096, 1.291], t = 1.766, p = 0.088
disp B = -0.027 [-0.049, -0.006], t = -2.574, p = 0.016
R² = 0.784 (adj = 0.76)(Intercept) B = 34.661 [31.149, 38.173], t = 19.737, p < 0.001
cyl B = -1.587 [-2.569, -0.606], t = -3.234, p = 0.002
disp B = -0.021 [-0.035, -0.006], t = -2.91, p = 0.005
R² = 0.76 (adj = 0.752)(Intercept) B = 34.661 [29.452, 39.87], t = 13.609, p < 0.001
cyl B = -1.587 [-3.043, -0.131], t = -2.23, p = 0.034
disp B = -0.021 [-0.042, 0], t = -2.007, p = 0.054
R² = 0.76 (adj = 0.743)(Intercept) B = -32.432 [-98.452, 33.589], t = -1.005, p = 0.323
cyl B = 24.515 [6.063, 42.966], t = 2.717, p = 0.011
disp B = 0.119 [-0.147, 0.385], t = 0.915, p = 0.368
R² = 0.702 (adj = 0.681)[ FAIL 1 | WARN 7 | SKIP 27 | PASS 339 ]
══ Skipped tests (27) ══════════════════════════════════════════════════════════
• empty test (27): 'test_poly.r:6:1', 'test_umxBuild_run_modify.r:94:1',
'test_umxBuild_run_modify.r:131:1', 'test_umxBuild_run_modify.r:150:1',
'test_umxBuild_run_modify.r:195:1', 'test_umxCP.r:4:1',
'test_umxFactorScores.r:9:1', 'test_umxFitAndReporting.r:191:1',
'test_umxFitAndReporting.r:205:1', 'test_umxMatrixFree.R:6:1',
'test_umxPath.r:7:1', 'test_umx_ACE_etc.r:6:1', 'test_umx_ACE_etc.r:26:1',
'test_umx_ACE_etc.r:69:2', 'test_umx_ACE_etc.r:118:2',
'test_umx_ACE_etc.r:135:2', 'test_umx_ACE_etc.r:163:2',
'test_umx_ACE_etc.r:185:2', 'test_umx_ACE_etc.r:222:1',
'test_umx_ACE_etc.r:236:1', 'test_umx_ACE_etc.r:248:1',
'test_umx_CLPM.r:6:1', 'test_umx_DOC_etc.r:6:1', 'test_umx_misc.r:54:1',
'test_umx_misc.r:96:1', 'test_umx_misc.r:111:1', 'test_umx_misc.r:161:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_umxPower.r:36:2'): umxPower works ──────────────────────────────
Error in `grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y,
resolveHJust(x$just, x$hjust), resolveVJust(x$just, x$vjust),
x$rot, as.numeric(NA))`: conversion failure on 'Power = 1 - β' in 'mbcsToSbcs': for β (U+03B2)
Backtrace:
▆
1. ├─umx::umxPower(m1, "X_with_Y", explore = TRUE) at test_umxPower.r:36:9
2. │ ├─base::print(p)
3. │ ├─base::print(p)
4. │ └─ggplot2:::print.ggplot(p)
5. │ ├─grid::grid.draw(gtable)
6. │ └─grid:::grid.draw.gTree(gtable)
7. │ └─grDevices::recordGraphics(drawGTree(x), list(x = x), getNamespace("grid"))
8. ├─grid:::drawGTree(x)
9. │ ├─grid:::preDraw(x)
10. │ └─grid:::preDraw.gTree(x)
11. │ └─grid:::pushvpgp(x)
12. │ ├─grid:::pushgrobvp(x$vp)
13. │ └─grid:::pushgrobvp.viewport(x$vp)
14. │ └─grid::pushViewport(vp, recording = FALSE)
15. │ └─base::lapply(vps, push.vp, recording)
16. │ ├─grid (local) FUN(X[[i]], ...)
17. │ └─grid:::push.vp.viewport(X[[i]], ...)
18. │ └─grid:::grid.Call.graphics(C_setviewport, vp, TRUE)
19. ├─grid (local) `<fn>`(`<titleGrb>`)
20. ├─grid:::preDraw.gTree(`<titleGrb>`)
21. │ └─grid:::pushvpgp(x)
22. │ ├─grid:::pushgrobvp(x$vp)
23. │ └─grid:::pushgrobvp.viewport(x$vp)
24. │ └─grid::pushViewport(vp, recording = FALSE)
25. │ └─base::lapply(vps, push.vp, recording)
26. │ ├─grid (local) FUN(X[[i]], ...)
27. │ └─grid:::push.vp.vpTree(X[[i]], ...)
28. │ ├─grid:::push.vp(vp$parent, recording)
29. │ └─grid:::push.vp.viewport(vp$parent, recording)
30. │ └─grid:::grid.Call.graphics(C_setviewport, vp, TRUE)
31. └─grid (local) `<fn>`(`<text>`)
32. ├─grid::widthDetails(x)
33. └─grid:::widthDetails.text(x)
34. └─grid:::grid.Call(...)
[ FAIL 1 | WARN 7 | SKIP 27 | PASS 339 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 4.16.0
Check: installed package size
Result: NOTE
installed size is 6.0Mb
sub-directories of 1Mb or more:
R 1.0Mb
help 4.4Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-windows-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 4.16.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [9m/23m]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library("testthat")
> library("umx")
Loading required package: OpenMx
To take full advantage of multiple cores, use:
mxOption(key='Number of Threads', value=parallel::detectCores()) #now
Sys.setenv(OMP_NUM_THREADS=parallel::detectCores()) #before library(OpenMx)
For an overview type '?umx'
Attaching package: 'umx'
The following object is masked from 'package:stats':
loadings
>
> test_check("umx")
OMP: Warning #96: Cannot form a team with 22 threads, using 2 instead.
OMP: Hint Consider unsetting KMP_DEVICE_THREAD_LIMIT (KMP_ALL_THREADS), KMP_TEAMS_THREAD_LIMIT, and OMP_THREAD_LIMIT (if any are set).
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:------|--:|:-----|:----|:-------|--------:|:-----|:------------------|:---------|
|CP3fac | 51| | | | 184511.4|0 | |-2lnL |
|dropC | 42|233.3 |9 |< 0.001 | 184726.7|215.3 |CP3fac |-2lnL |
Table: Common Factor Paths
| | A|C | E|
|:---------------|----:|:--|----:|
|Common.factor.1 | 0.79|. | 0.62|
|Common.factor.2 | 0.65|. | 0.76|
|Common.factor.3 | 0.29|. | 0.96|
Table: Loadings of each trait on the Common Factors
| | CP1| CP2| CP3|
|:---|-----:|-----:|-----:|
|gff | 0.44| 0.34| 0.08|
|fc | 0.98| -0.05| 0.02|
|qol | 0.31| 0.71| 0.10|
|hap | 0.24| 0.52| 0.82|
|sat | 0.27| 0.61| 0.43|
|AD | -0.31| -0.43| -0.23|
Table: Specific-factor loadings
| |gff |fc |qol |hap |sat |AD |
|:----------|:----|:----|:----|:---|:----|:----|
|Specific a |0.45 |. |0.14 |. |0.17 |0.38 |
|Specific c |. |. |. |. |. |. |
|Specific e |0.7 |0.16 |0.61 |. |0.59 |0.73 |
Table: Means (from model$top$expMean)
| | gff_T1| fc_T1| qol_T1| hap_T1| sat_T1| AD_T1| gff_T2| fc_T2| qol_T2| hap_T2| sat_T2| AD_T2|
|:---------|------:|------:|------:|------:|------:|-----:|------:|------:|------:|------:|------:|-----:|
|intercept | 38.39| -13.37| 7.81| 22.97| 27.56| 4.09| 38.39| -13.37| 7.81| 22.97| 27.56| 4.09|
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:------|--:|:-------|:----|:-------|--------:|:-------|:------------------|:---------|
|CP3fac | 51| | | | 184511.4|0 | |-2lnL |
|dropC | 42|233.302 |9 |< 0.001 | 184726.7|215.302 |CP3fac |-2lnL |
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
G_to_x2 0.469 0.503 0.541 0 0
G_to_x3 0.538 0.577 0.619 0 0
G_to_x4 0.657 0.702 0.751 0 0
G_to_x5 0.746 0.795 0.850 0 0
x1_with_x1 0.036 0.041 0.047 0 0
x2_with_x2 0.033 0.038 0.044 0 0
x3_with_x3 0.035 0.041 0.047 0 0
x4_with_x4 0.033 0.039 0.047 0 0
x5_with_x5 0.030 0.036 0.044 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
G_to_x2 0.469 0.503 0.541 0 0
G_to_x3 0.538 0.577 0.619 0 0
G_to_x4 0.657 0.702 0.751 0 0
G_to_x5 0.746 0.795 0.850 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
The hypothesis that 'drop_path_2_x2' was tested by dropping drop_path_2_x2 from 'One Factor'. This caused a significant loss of fit (χ²(1) = 946, p = < 0.001: AIC = -2696.599 change in AIC = 943.998).
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------|--:|:-------|:----|:-------|---------:|:-------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------|--:|:-------|:----|:-------|---------:|:-------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
<table class=" lightable-paper lightable-striped" style='font-family: "Arial Narrow", arial, helvetica, sans-serif; width: auto !important; margin-left: auto; margin-right: auto;'>
<caption>Table of Model Comparisons</caption>
<thead>
<tr>
<th style="text-align:left;"> Model </th>
<th style="text-align:right;"> EP </th>
<th style="text-align:left;"> Δ Fit </th>
<th style="text-align:left;"> Δ df </th>
<th style="text-align:left;"> p </th>
<th style="text-align:right;"> AIC </th>
<th style="text-align:left;"> Δ AIC </th>
<th style="text-align:left;"> Compare with Model </th>
<th style="text-align:left;"> Fit units </th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;"> One Factor </td>
<td style="text-align:right;"> 10 </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> </td>
<td style="text-align:right;"> -3640.597 </td>
<td style="text-align:left;"> 0 </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> -2lnL </td>
</tr>
<tr>
<td style="text-align:left;"> drop_path_2_x2 </td>
<td style="text-align:right;"> 9 </td>
<td style="text-align:left;"> 945.998 </td>
<td style="text-align:left;"> 1 </td>
<td style="text-align:left;"> < 0.001 </td>
<td style="text-align:right;"> -2696.599 </td>
<td style="text-align:left;"> 943.998 </td>
<td style="text-align:left;"> One Factor </td>
<td style="text-align:left;"> -2lnL </td>
</tr>
</tbody>
</table>
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
The 'One Factor' model is the best fitting model according to AIC.AIC weight-based {Wagenmakers, 2004, 192-196} conditional probabilities of being the best model for 'One Factor', 'drop_path_2_x2', and 'drop_path_2_x2_and_3' respectively are: '1', '0', and '0' Using MuMIn::Weights(AIC()).
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
|drop_path_2_x2 | 9| | | | -2696.599|943.998 | |-2lnL |
|drop_path_2_x2 | 9|0 |0 | | -2696.599|943.998 |drop_path_2_x2 |-2lnL |
|drop_path_2_x2_and_3 | 8|993.341 |1 |< 0.001 | -1705.258|1935.339 |drop_path_2_x2 |-2lnL |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:----------|------------:|:------|:-----------------|:---------------|
|11 |G_with_G | 1.00|0 |1 [1, 1] |Factor Variance |
|1 |G_to_x1 | 0.89|0.01 |0.89 [0.87, 0.91] |Factor loading |
|2 |G_to_x2 | 0.93|0.01 |0.93 [0.92, 0.95] |Factor loading |
|3 |G_to_x3 | 0.94|0.01 |0.94 [0.93, 0.95] |Factor loading |
|4 |G_to_x4 | 0.96|0 |0.96 [0.95, 0.97] |Factor loading |
|5 |G_to_x5 | 0.97|0 |0.97 [0.97, 0.98] |Factor loading |
|6 |x1_with_x1 | 0.21|0.02 |0.21 [0.17, 0.24] |Residual |
|7 |x2_with_x2 | 0.13|0.01 |0.13 [0.11, 0.15] |Residual |
|8 |x3_with_x3 | 0.11|0.01 |0.11 [0.09, 0.13] |Residual |
|9 |x4_with_x4 | 0.07|0.01 |0.07 [0.06, 0.09] |Residual |
|10 |x5_with_x5 | 0.05|0.01 |0.05 [0.04, 0.07] |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:----------|------------:|:------|:-----------------|:---------------|
|11 |G_with_G | 1.00|0 |1 [1, 1] |Factor Variance |
|1 |G_to_x1 | 0.89|0.01 |0.89 [0.87, 0.91] |Factor loading |
|2 |G_to_x2 | 0.93|0.01 |0.93 [0.92, 0.95] |Factor loading |
|3 |G_to_x3 | 0.94|0.01 |0.94 [0.93, 0.95] |Factor loading |
|4 |G_to_x4 | 0.96|0 |0.96 [0.95, 0.97] |Factor loading |
|5 |G_to_x5 | 0.97|0 |0.97 [0.97, 0.98] |Factor loading |
|6 |x1_with_x1 | 0.21|0.02 |0.21 [0.17, 0.24] |Residual |
|7 |x2_with_x2 | 0.13|0.01 |0.13 [0.11, 0.15] |Residual |
|8 |x3_with_x3 | 0.11|0.01 |0.11 [0.09, 0.13] |Residual |
|9 |x4_with_x4 | 0.07|0.01 |0.07 [0.06, 0.09] |Residual |
|10 |x5_with_x5 | 0.05|0.01 |0.05 [0.04, 0.07] |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Estimate|SE |type |
|:--|:----------|--------:|:----|:---------------|
|11 |G_with_G | 1.00|0 |Factor Variance |
|1 |G_to_x1 | 0.40|0.02 |Factor loading |
|2 |G_to_x2 | 0.50|0.02 |Factor loading |
|3 |G_to_x3 | 0.58|0.02 |Factor loading |
|4 |G_to_x4 | 0.70|0.02 |Factor loading |
|5 |G_to_x5 | 0.80|0.03 |Factor loading |
|6 |x1_with_x1 | 0.04|0 |Residual |
|7 |x2_with_x2 | 0.04|0 |Residual |
|8 |x3_with_x3 | 0.04|0 |Residual |
|9 |x4_with_x4 | 0.04|0 |Residual |
|10 |x5_with_x5 | 0.04|0 |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate| Std.SE|CI |type |
|:--|:---------|------------:|------:|:-------------------|:----|
|12 |one_to_x1 | -0.02| 0.1|-0.02 [-0.22, 0.18] |Mean |
|13 |one_to_x2 | -0.10| 0.1|-0.1 [-0.3, 0.1] |Mean |
|14 |one_to_x3 | -0.08| 0.1|-0.08 [-0.28, 0.11] |Mean |
|15 |one_to_x4 | -0.07| 0.1|-0.07 [-0.27, 0.12] |Mean |
|16 |one_to_x5 | -0.07| 0.1|-0.07 [-0.26, 0.13] |Mean |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |-0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |-0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |-0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |-0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |-0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |-0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |-0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |-0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |-0.07 |0.24 |
|e_r1c1 |0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |-0.01 |0.01 |
|em_r1c1 |0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
Table: General Independent Pathway path loadings
| | ai1| ci1| ei1|
|:---|-----:|-----:|-----:|
|hap | 0.47| 0.24| 0.77|
|sat | 0.51| 0.20| 0.56|
|AD | -0.54| -0.06| -0.27|
Table: Specific factor loadings
| |hap |sat |AD |
|:----------|:----|:----|:----|
|Specific a |0.14 |0.3 |0.45 |
|Specific c |. |. |. |
|Specific e |0.32 |0.54 |0.65 |
Table: Means (from model$top$expMean)
| | hap_T1| sat_T1| AD_T1| hap_T2| sat_T2| AD_T2|
|:---------|------:|------:|-----:|------:|------:|-----:|
|intercept | 22.98| 27.56| 4.14| 22.98| 27.56| 4.14|
Table: Parameter loadings for model 'tim'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:------------------|------------:|:------|:--------------------|:-------------|
|5 |litres_with_wt | 0.89|0.04 |0.89 [0.81, 0.96] |Manifest Cov |
|1 |wt_to_mpg | -0.54|0.17 |-0.54 [-0.89, -0.2] |Manifest path |
|2 |litres_to_mpg | -0.36|0.18 |-0.36 [-0.71, -0.02] |Manifest path |
|7 |one_to_mpg | 5.89|0.68 |5.89 [4.56, 7.22] |Mean |
|8 |one_to_wt | 3.34|0.45 |3.34 [2.45, 4.23] |Mean |
|9 |one_to_litres | 1.89|0.3 |1.89 [1.31, 2.47] |Mean |
|3 |mpg_with_mpg | 0.22|0.07 |0.22 [0.08, 0.35] |Residual |
|4 |wt_with_wt | 1.00|0 |1 [1, 1] |Residual |
|6 |litres_with_litres | 1.00|0 |1 [1, 1] |Residual |
Table: Raw parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1| c1| e1|
|:--|----:|---:|----:|
|ht | 0.61| 0.1| 0.24|
Table: Means (from model$top$expMean)
| | ht1| ht2|
|:---------|------:|------:|
|intercept | 16.252| 16.252|
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:-----|--:|:------|:----|:--|--------:|:------|:------------------|:---------|
|ADE | 4| | | | 5987.341|0 | |-2lnL |
|ACE | 4|-0.139 |0 | | 5987.202|-0.139 |ADE |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:-----|--:|:-----|:----|:--|-------:|:-----|:------------------|:---------|
|ACE | 4| | | | 5987.20|0 | |-2lnL |
|ADE | 4|0.14 |0 | | 5987.34|0.14 |ACE |-2lnL |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; D: dominance effects; E: unique environment.
| | a1|d1 | e1|
|:--|----:|:--|----:|
|ht | 0.93|. | 0.36|
Table: Means (from model$top$expMean)
| | ht1| ht2|
|:---------|------:|------:|
|intercept | 16.252| 16.252|
(Intercept) B = 60.201 [59.505, 60.898], t = 169.359, p < 0.001
age B = 0.106 [0.088, 0.125], t = 11.183, p < 0.001
R² = 0.017 (adj = 0.016)(Intercept) B = 1.711 [1.705, 1.717], t = 590.26, p < 0.001
age B = -0.001 [-0.001, -0.001], t = -12.358, p < 0.001
R² = 0.02 (adj = 0.02)
Table: Standardized parameter estimates from a 2-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|a2 | c1|c2 | e1|e2 |
|:--|----:|:----|-----:|:--|----:|:---|
|ht | 0.76| | 0.43| | 0.49| |
|wt | 0.60|0.68 | -0.10|. | 0.02|0.4 |
Table: Means (from model$top$expMean)
| | ht1| wt1| ht2| wt2|
|:---------|-----:|------:|-----:|------:|
|intercept | -0.39| -0.532| -0.39| -0.532|
'data.frame': 80 obs. of 18 variables:
$ fam : int 1 2 3 4 5 6 7 8 9 10 ...
$ age : int 21 24 21 21 19 26 23 29 24 28 ...
$ zyg : int 1 1 1 1 1 1 1 1 1 1 ...
$ part : int 2 2 2 2 2 2 2 2 2 2 ...
$ wt1 : num -0.502 -0.844 -0.758 0.181 -1.185 ...
$ wt2 : num -0.588 -0.929 -1.185 1.035 -1.356 ...
$ ht1 : num 1.7 1.63 1.65 1.57 1.61 ...
$ ht2 : num 1.7 1.63 1.68 1.65 1.63 ...
$ htwt1 : num 20.1 20.3 20.2 26.8 19.3 ...
$ htwt2 : num 19.7 19.9 17.7 27.9 18.1 ...
$ bmi1 : num 21 21.1 21 23 20.7 ...
$ bmi2 : num 20.9 21 20.1 23.3 20.3 ...
$ cohort : chr "younger" "younger" "younger" "younger" ...
$ zygosity: Factor w/ 5 levels "MZFF","MZMM",..: 1 1 1 1 1 1 1 1 1 1 ...
$ age1 : int 21 24 21 21 19 26 23 29 24 28 ...
$ age2 : int 21 24 21 21 19 26 23 29 24 28 ...
$ obese1 : Ord.factor w/ 3 levels "normal"<"overweight"<..: 2 2 2 3 1 3 2 1 1 3 ...
$ obese2 : Ord.factor w/ 3 levels "normal"<"overweight"<..: 1 1 1 3 1 3 2 1 1 2 ...
Table: Standardized parameter estimates from a 2-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|a2 | c1|c2 | e1|e2 |
|:-----|----:|:----|----:|:--|----:|:----|
|wt | 0.87| | 0.06| | 0.48| |
|obese | 0.63|0.52 | 0.25|. | 0.40|0.33 |
Table: Means (from model$top$expMean)
| | wt1|obese1 | wt2|obese2 |
|:---------|------:|:------|------:|:------|
|intercept | -0.414|0 | -0.414|0 |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:--|----:|:--|----:|
|wt | 0.87|. | 0.49|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.698| 21.698|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.45|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.305| 21.305|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.45|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.313| 21.313|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.46|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.32| 21.32|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.46|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.329| 21.329|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.47|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.34| 21.34|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.47|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.351| 21.351|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.48|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.364| 21.364|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.48|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.378| 21.378|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.394| 21.394|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.411| 21.411|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.429| 21.429|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.449| 21.449|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.47| 21.47|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.492| 21.492|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.514| 21.514|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.536| 21.536|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.558| 21.558|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.58| 21.58|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.601| 21.601|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.621| 21.621|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.641| 21.641|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.66| 21.66|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.679| 21.679|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.698| 21.698|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.718| 21.718|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.739| 21.739|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|----:|
|bmi |. | 0.8| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.763| 21.763|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.788| 21.788|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.816| 21.816|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.847| 21.847|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.88| 21.88|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|----:|
|bmi |. | 0.8| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.914| 21.914|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.949| 21.949|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.985| 21.985|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.019| 22.019|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.051| 22.051|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.081| 22.081|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.108| 22.108|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.131| 22.131|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.152| 22.152|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 22.17| 22.17|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.185| 22.185|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.197| 22.197|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.208| 22.208|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.216| 22.216|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.223| 22.223|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.229| 22.229|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.233| 22.233|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.238| 22.238|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.242| 22.242|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.86| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.246| 22.246|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.251| 22.251|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.256| 22.256|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.261| 22.261|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.266| 22.266|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 22.27| 22.27|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.272| 22.272|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.272| 22.272|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.268| 22.268|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.259| 22.259|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.244| 22.244|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.223| 22.223|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.194| 22.194|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.158| 22.158|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.115| 22.115|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.78| 0.62|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.066| 22.066|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.76| 0.66|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.015| 22.015|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.72| 0.69|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.961| 21.961|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.68| 0.73|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.909| 21.909|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.63| 0.77|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.859| 21.859|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.58| 0.81|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.814| 21.814|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.53| 0.85|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.776| 21.776|
polite note: in future, please use report = 'markdown', not file='markdown'. file is for choosing a custom html file when writing to the browser with report= 'html'
Table: Standardized parameter estimates from a 1-factor Direct variance ACE model. A: additive genetic; C: common environment; E: unique environment.
| | A1| C1| E1|
|:---|-----:|------:|-----:|
|bmi | 0.807| -0.063| 0.256|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.649| 21.649|
Table: Parameter loadings for model 'check_model_ex'
| |name | Estimate|SE |type |
|:--|:----------|--------:|:----|:---------------|
|11 |G_with_G | 1.00|0 |Factor Variance |
|1 |G_to_x1 | 0.89|0.02 |Factor loading |
|2 |G_to_x2 | 0.93|0.02 |Factor loading |
|3 |G_to_x3 | 0.94|0.02 |Factor loading |
|4 |G_to_x4 | 0.96|0.02 |Factor loading |
|5 |G_to_x5 | 0.97|0.03 |Factor loading |
|6 |x1_with_x1 | 0.21|0 |Residual |
|7 |x2_with_x2 | 0.13|0 |Residual |
|8 |x3_with_x3 | 0.11|0 |Residual |
|9 |x4_with_x4 | 0.07|0 |Residual |
|10 |x5_with_x5 | 0.05|0 |Residual |
[1] "cyl"
[1] "cylinder"
(Intercept) B = 34.661 [29.452, 39.87], t = 13.609, p < 0.001
cyl B = -1.587 [-3.043, -0.131], t = -2.23, p = 0.034
disp B = -0.021 [-0.042, 0], t = -2.007, p = 0.054
R² = 0.76 (adj = 0.743)(Intercept) B = 53.445 [31.077, 75.814], t = 4.894, p < 0.001
cyl B = -8.367 [-16.359, -0.376], t = -2.145, p = 0.041
I(cyl^2) B = 0.597 [-0.096, 1.291], t = 1.766, p = 0.088
disp B = -0.027 [-0.049, -0.006], t = -2.574, p = 0.016
R² = 0.784 (adj = 0.76)(Intercept) B = 34.661 [31.149, 38.173], t = 19.737, p < 0.001
cyl B = -1.587 [-2.569, -0.606], t = -3.234, p = 0.002
disp B = -0.021 [-0.035, -0.006], t = -2.91, p = 0.005
R² = 0.76 (adj = 0.752)(Intercept) B = 34.661 [29.452, 39.87], t = 13.609, p < 0.001
cyl B = -1.587 [-3.043, -0.131], t = -2.23, p = 0.034
disp B = -0.021 [-0.042, 0], t = -2.007, p = 0.054
R² = 0.76 (adj = 0.743)(Intercept) B = -32.432 [-98.452, 33.589], t = -1.005, p = 0.323
cyl B = 24.515 [6.063, 42.966], t = 2.717, p = 0.011
disp B = 0.119 [-0.147, 0.385], t = 0.915, p = 0.368
R² = 0.702 (adj = 0.681)[ FAIL 1 | WARN 7 | SKIP 27 | PASS 339 ]
══ Skipped tests (27) ══════════════════════════════════════════════════════════
• empty test (27): 'test_poly.r:6:1', 'test_umxBuild_run_modify.r:94:1',
'test_umxBuild_run_modify.r:131:1', 'test_umxBuild_run_modify.r:150:1',
'test_umxBuild_run_modify.r:195:1', 'test_umxCP.r:4:1',
'test_umxFactorScores.r:9:1', 'test_umxFitAndReporting.r:191:1',
'test_umxFitAndReporting.r:205:1', 'test_umxMatrixFree.R:6:1',
'test_umxPath.r:7:1', 'test_umx_ACE_etc.r:6:1', 'test_umx_ACE_etc.r:26:1',
'test_umx_ACE_etc.r:69:2', 'test_umx_ACE_etc.r:118:2',
'test_umx_ACE_etc.r:135:2', 'test_umx_ACE_etc.r:163:2',
'test_umx_ACE_etc.r:185:2', 'test_umx_ACE_etc.r:222:1',
'test_umx_ACE_etc.r:236:1', 'test_umx_ACE_etc.r:248:1',
'test_umx_CLPM.r:6:1', 'test_umx_DOC_etc.r:6:1', 'test_umx_misc.r:54:1',
'test_umx_misc.r:96:1', 'test_umx_misc.r:111:1', 'test_umx_misc.r:161:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_umxPower.r:36:2'): umxPower works ──────────────────────────────
Error in `grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y,
resolveHJust(x$just, x$hjust), resolveVJust(x$just, x$vjust),
x$rot, as.numeric(NA))`: conversion failure on 'Power = 1 - β' in 'mbcsToSbcs': for β (U+03B2)
Backtrace:
▆
1. ├─umx::umxPower(m1, "X_with_Y", explore = TRUE) at test_umxPower.r:36:9
2. │ ├─base::print(p)
3. │ ├─base::print(p)
4. │ └─ggplot2:::print.ggplot(p)
5. │ ├─grid::grid.draw(gtable)
6. │ └─grid:::grid.draw.gTree(gtable)
7. │ └─grDevices::recordGraphics(drawGTree(x), list(x = x), getNamespace("grid"))
8. ├─grid:::drawGTree(x)
9. │ ├─grid:::preDraw(x)
10. │ └─grid:::preDraw.gTree(x)
11. │ └─grid:::pushvpgp(x)
12. │ ├─grid:::pushgrobvp(x$vp)
13. │ └─grid:::pushgrobvp.viewport(x$vp)
14. │ └─grid::pushViewport(vp, recording = FALSE)
15. │ └─base::lapply(vps, push.vp, recording)
16. │ ├─grid (local) FUN(X[[i]], ...)
17. │ └─grid:::push.vp.viewport(X[[i]], ...)
18. │ └─grid:::grid.Call.graphics(C_setviewport, vp, TRUE)
19. ├─grid (local) `<fn>`(`<titleGrb>`)
20. ├─grid:::preDraw.gTree(`<titleGrb>`)
21. │ └─grid:::pushvpgp(x)
22. │ ├─grid:::pushgrobvp(x$vp)
23. │ └─grid:::pushgrobvp.viewport(x$vp)
24. │ └─grid::pushViewport(vp, recording = FALSE)
25. │ └─base::lapply(vps, push.vp, recording)
26. │ ├─grid (local) FUN(X[[i]], ...)
27. │ └─grid:::push.vp.vpTree(X[[i]], ...)
28. │ ├─grid:::push.vp(vp$parent, recording)
29. │ └─grid:::push.vp.viewport(vp$parent, recording)
30. │ └─grid:::grid.Call.graphics(C_setviewport, vp, TRUE)
31. └─grid (local) `<fn>`(`<text>`)
32. ├─grid::widthDetails(x)
33. └─grid:::widthDetails.text(x)
34. └─grid:::grid.Call(...)
[ FAIL 1 | WARN 7 | SKIP 27 | PASS 339 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 4.16.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [549s/553s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library("testthat")
> library("umx")
Loading required package: OpenMx
To take full advantage of multiple cores, use:
mxOption(key='Number of Threads', value=parallel::detectCores()) #now
Sys.setenv(OMP_NUM_THREADS=parallel::detectCores()) #before library(OpenMx)
For an overview type '?umx'
Attaching package: 'umx'
The following object is masked from 'package:stats':
loadings
>
> test_check("umx")
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:------|--:|:-----|:----|:-------|--------:|:-----|:------------------|:---------|
|CP3fac | 51| | | | 184511.4|0 | |-2lnL |
|dropC | 42|233.3 |9 |< 0.001 | 184726.7|215.3 |CP3fac |-2lnL |
Table: Common Factor Paths
| | A|C | E|
|:---------------|----:|:--|----:|
|Common.factor.1 | 0.79|. | 0.62|
|Common.factor.2 | 0.65|. | 0.76|
|Common.factor.3 | 0.29|. | 0.96|
Table: Loadings of each trait on the Common Factors
| | CP1| CP2| CP3|
|:---|-----:|-----:|-----:|
|gff | 0.44| 0.34| 0.08|
|fc | 0.98| -0.05| 0.02|
|qol | 0.31| 0.71| 0.10|
|hap | 0.24| 0.52| 0.82|
|sat | 0.27| 0.61| 0.43|
|AD | -0.31| -0.43| -0.23|
Table: Specific-factor loadings
| |gff |fc |qol |hap |sat |AD |
|:----------|:----|:----|:----|:---|:----|:----|
|Specific a |0.45 |. |0.14 |. |0.17 |0.38 |
|Specific c |. |. |. |. |. |. |
|Specific e |0.7 |0.16 |0.61 |. |0.59 |0.73 |
Table: Means (from model$top$expMean)
| | gff_T1| fc_T1| qol_T1| hap_T1| sat_T1| AD_T1| gff_T2| fc_T2| qol_T2| hap_T2| sat_T2| AD_T2|
|:---------|------:|------:|------:|------:|------:|-----:|------:|------:|------:|------:|------:|-----:|
|intercept | 38.39| -13.37| 7.81| 22.97| 27.56| 4.09| 38.39| -13.37| 7.81| 22.97| 27.56| 4.09|
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:------|--:|:-------|:----|:-------|--------:|:-------|:------------------|:---------|
|CP3fac | 51| | | | 184511.4|0 | |-2lnL |
|dropC | 42|233.302 |9 |< 0.001 | 184726.7|215.302 |CP3fac |-2lnL |
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
G_to_x2 0.469 0.503 0.541 0 0
G_to_x3 0.538 0.577 0.619 0 0
G_to_x4 0.657 0.702 0.751 0 0
G_to_x5 0.746 0.795 0.850 0 0
x1_with_x1 0.036 0.041 0.047 0 0
x2_with_x2 0.033 0.038 0.044 0 0
x3_with_x3 0.035 0.041 0.047 0 0
x4_with_x4 0.033 0.039 0.047 0 0
x5_with_x5 0.030 0.036 0.044 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
G_to_x2 0.469 0.503 0.541 0 0
G_to_x3 0.538 0.577 0.619 0 0
G_to_x4 0.657 0.702 0.751 0 0
G_to_x5 0.746 0.795 0.850 0 0
lbound estimate ubound lbound Code ubound Code
G_to_x1 0.367 0.397 0.429 0 0
The hypothesis that 'drop_path_2_x2' was tested by dropping drop_path_2_x2 from 'One Factor'. This caused a significant loss of fit (χ²(1) = 946, p = < 0.001: AIC = -2696.599 change in AIC = 943.998).
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------|--:|:-------|:----|:-------|---------:|:-------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------|--:|:-------|:----|:-------|---------:|:-------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
<table class=" lightable-paper lightable-striped" style='font-family: "Arial Narrow", arial, helvetica, sans-serif; width: auto !important; margin-left: auto; margin-right: auto;'>
<caption>Table of Model Comparisons</caption>
<thead>
<tr>
<th style="text-align:left;"> Model </th>
<th style="text-align:right;"> EP </th>
<th style="text-align:left;"> Δ Fit </th>
<th style="text-align:left;"> Δ df </th>
<th style="text-align:left;"> p </th>
<th style="text-align:right;"> AIC </th>
<th style="text-align:left;"> Δ AIC </th>
<th style="text-align:left;"> Compare with Model </th>
<th style="text-align:left;"> Fit units </th>
</tr>
</thead>
<tbody>
<tr>
<td style="text-align:left;"> One Factor </td>
<td style="text-align:right;"> 10 </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> </td>
<td style="text-align:right;"> -3640.597 </td>
<td style="text-align:left;"> 0 </td>
<td style="text-align:left;"> </td>
<td style="text-align:left;"> -2lnL </td>
</tr>
<tr>
<td style="text-align:left;"> drop_path_2_x2 </td>
<td style="text-align:right;"> 9 </td>
<td style="text-align:left;"> 945.998 </td>
<td style="text-align:left;"> 1 </td>
<td style="text-align:left;"> < 0.001 </td>
<td style="text-align:right;"> -2696.599 </td>
<td style="text-align:left;"> 943.998 </td>
<td style="text-align:left;"> One Factor </td>
<td style="text-align:left;"> -2lnL </td>
</tr>
</tbody>
</table>
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
The 'One Factor' model is the best fitting model according to AIC.AIC weight-based {Wagenmakers, 2004, 192-196} conditional probabilities of being the best model for 'One Factor', 'drop_path_2_x2', and 'drop_path_2_x2_and_3' respectively are: '1', '0', and '0' Using MuMIn::Weights(AIC()).
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:--------------------|--:|:--------|:----|:-------|---------:|:--------|:------------------|:---------|
|One Factor | 10| | | | -3640.597|0 | |-2lnL |
|drop_path_2_x2 | 9|945.998 |1 |< 0.001 | -2696.599|943.998 |One Factor |-2lnL |
|drop_path_2_x2_and_3 | 8|1939.339 |2 |< 0.001 | -1705.258|1935.339 |One Factor |-2lnL |
|drop_path_2_x2 | 9| | | | -2696.599|943.998 | |-2lnL |
|drop_path_2_x2 | 9|0 |0 | | -2696.599|943.998 |drop_path_2_x2 |-2lnL |
|drop_path_2_x2_and_3 | 8|993.341 |1 |< 0.001 | -1705.258|1935.339 |drop_path_2_x2 |-2lnL |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:----------|------------:|:------|:-----------------|:---------------|
|11 |G_with_G | 1.00|0 |1 [1, 1] |Factor Variance |
|1 |G_to_x1 | 0.89|0.01 |0.89 [0.87, 0.91] |Factor loading |
|2 |G_to_x2 | 0.93|0.01 |0.93 [0.92, 0.95] |Factor loading |
|3 |G_to_x3 | 0.94|0.01 |0.94 [0.93, 0.95] |Factor loading |
|4 |G_to_x4 | 0.96|0 |0.96 [0.95, 0.97] |Factor loading |
|5 |G_to_x5 | 0.97|0 |0.97 [0.97, 0.98] |Factor loading |
|6 |x1_with_x1 | 0.21|0.02 |0.21 [0.17, 0.24] |Residual |
|7 |x2_with_x2 | 0.13|0.01 |0.13 [0.11, 0.15] |Residual |
|8 |x3_with_x3 | 0.11|0.01 |0.11 [0.09, 0.13] |Residual |
|9 |x4_with_x4 | 0.07|0.01 |0.07 [0.06, 0.09] |Residual |
|10 |x5_with_x5 | 0.05|0.01 |0.05 [0.04, 0.07] |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:----------|------------:|:------|:-----------------|:---------------|
|11 |G_with_G | 1.00|0 |1 [1, 1] |Factor Variance |
|1 |G_to_x1 | 0.89|0.01 |0.89 [0.87, 0.91] |Factor loading |
|2 |G_to_x2 | 0.93|0.01 |0.93 [0.92, 0.95] |Factor loading |
|3 |G_to_x3 | 0.94|0.01 |0.94 [0.93, 0.95] |Factor loading |
|4 |G_to_x4 | 0.96|0 |0.96 [0.95, 0.97] |Factor loading |
|5 |G_to_x5 | 0.97|0 |0.97 [0.97, 0.98] |Factor loading |
|6 |x1_with_x1 | 0.21|0.02 |0.21 [0.17, 0.24] |Residual |
|7 |x2_with_x2 | 0.13|0.01 |0.13 [0.11, 0.15] |Residual |
|8 |x3_with_x3 | 0.11|0.01 |0.11 [0.09, 0.13] |Residual |
|9 |x4_with_x4 | 0.07|0.01 |0.07 [0.06, 0.09] |Residual |
|10 |x5_with_x5 | 0.05|0.01 |0.05 [0.04, 0.07] |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Estimate|SE |type |
|:--|:----------|--------:|:----|:---------------|
|11 |G_with_G | 1.00|0 |Factor Variance |
|1 |G_to_x1 | 0.40|0.02 |Factor loading |
|2 |G_to_x2 | 0.50|0.02 |Factor loading |
|3 |G_to_x3 | 0.58|0.02 |Factor loading |
|4 |G_to_x4 | 0.70|0.02 |Factor loading |
|5 |G_to_x5 | 0.80|0.03 |Factor loading |
|6 |x1_with_x1 | 0.04|0 |Residual |
|7 |x2_with_x2 | 0.04|0 |Residual |
|8 |x3_with_x3 | 0.04|0 |Residual |
|9 |x4_with_x4 | 0.04|0 |Residual |
|10 |x5_with_x5 | 0.04|0 |Residual |
Table: Parameter loadings for model 'One Factor'
| |name | Std.Estimate| Std.SE|CI |type |
|:--|:---------|------------:|------:|:-------------------|:----|
|12 |one_to_x1 | -0.02| 0.1|-0.02 [-0.22, 0.18] |Mean |
|13 |one_to_x2 | -0.10| 0.1|-0.1 [-0.3, 0.1] |Mean |
|14 |one_to_x3 | -0.08| 0.1|-0.08 [-0.28, 0.11] |Mean |
|15 |one_to_x4 | -0.07| 0.1|-0.07 [-0.27, 0.12] |Mean |
|16 |one_to_x5 | -0.07| 0.1|-0.07 [-0.26, 0.13] |Mean |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:---|----:|:--|----:|
|bmi | 0.86|. | 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.648| 21.648|
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |-0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |-0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |-0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |-0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |-0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |-0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |-0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |-0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
|name |Estimate |Std.Error |
|:-------|:--------|:---------|
|a_r1c1 |0.82 |0.1 |
|c_r1c1 |0.07 |0.24 |
|e_r1c1 |-0.31 |0.03 |
|am_r1c1 |0 |0 |
|cm_r1c1 |0.01 |0.01 |
|em_r1c1 |-0.01 |0 |
|mean |20.57 |0.15 |
|lin11 |0.05 |0.01 |
|quad11 |0 |0 |
Table: General Independent Pathway path loadings
| | ai1| ci1| ei1|
|:---|-----:|-----:|-----:|
|hap | 0.47| 0.24| 0.77|
|sat | 0.51| 0.20| 0.56|
|AD | -0.54| -0.06| -0.27|
Table: Specific factor loadings
| |hap |sat |AD |
|:----------|:----|:----|:----|
|Specific a |0.14 |0.3 |0.45 |
|Specific c |. |. |. |
|Specific e |0.32 |0.54 |0.65 |
Table: Means (from model$top$expMean)
| | hap_T1| sat_T1| AD_T1| hap_T2| sat_T2| AD_T2|
|:---------|------:|------:|-----:|------:|------:|-----:|
|intercept | 22.98| 27.56| 4.14| 22.98| 27.56| 4.14|
Table: Parameter loadings for model 'tim'
| |name | Std.Estimate|Std.SE |CI |type |
|:--|:------------------|------------:|:------|:--------------------|:-------------|
|5 |litres_with_wt | 0.89|0.04 |0.89 [0.81, 0.96] |Manifest Cov |
|1 |wt_to_mpg | -0.54|0.17 |-0.54 [-0.89, -0.2] |Manifest path |
|2 |litres_to_mpg | -0.36|0.18 |-0.36 [-0.71, -0.02] |Manifest path |
|7 |one_to_mpg | 5.89|0.68 |5.89 [4.56, 7.22] |Mean |
|8 |one_to_wt | 3.34|0.45 |3.34 [2.45, 4.23] |Mean |
|9 |one_to_litres | 1.89|0.3 |1.89 [1.31, 2.47] |Mean |
|3 |mpg_with_mpg | 0.22|0.07 |0.22 [0.08, 0.35] |Residual |
|4 |wt_with_wt | 1.00|0 |1 [1, 1] |Residual |
|6 |litres_with_litres | 1.00|0 |1 [1, 1] |Residual |
Table: Raw parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1| c1| e1|
|:--|----:|---:|----:|
|ht | 0.61| 0.1| 0.24|
Table: Means (from model$top$expMean)
| | ht1| ht2|
|:---------|------:|------:|
|intercept | 16.252| 16.252|
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:-----|--:|:------|:----|:--|--------:|:------|:------------------|:---------|
|ADE | 4| | | | 5987.341|0 | |-2lnL |
|ACE | 4|-0.139 |0 | | 5987.202|-0.139 |ADE |-2lnL |
Table: Table of Model Comparisons
|Model | EP|Δ Fit |Δ df |p | AIC|Δ AIC |Compare with Model |Fit units |
|:-----|--:|:-----|:----|:--|-------:|:-----|:------------------|:---------|
|ACE | 4| | | | 5987.20|0 | |-2lnL |
|ADE | 4|0.14 |0 | | 5987.34|0.14 |ACE |-2lnL |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; D: dominance effects; E: unique environment.
| | a1|d1 | e1|
|:--|----:|:--|----:|
|ht | 0.93|. | 0.36|
Table: Means (from model$top$expMean)
| | ht1| ht2|
|:---------|------:|------:|
|intercept | 16.252| 16.252|
(Intercept) B = 60.201 [59.505, 60.898], t = 169.359, p < 0.001
age B = 0.106 [0.088, 0.125], t = 11.183, p < 0.001
R² = 0.017 (adj = 0.016)(Intercept) B = 1.711 [1.705, 1.717], t = 590.26, p < 0.001
age B = -0.001 [-0.001, -0.001], t = -12.358, p < 0.001
R² = 0.02 (adj = 0.02)
Table: Standardized parameter estimates from a 2-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|a2 | c1|c2 | e1|e2 |
|:--|----:|:----|-----:|:--|----:|:---|
|ht | 0.76| | 0.43| | 0.49| |
|wt | 0.60|0.68 | -0.10|. | 0.02|0.4 |
Table: Means (from model$top$expMean)
| | ht1| wt1| ht2| wt2|
|:---------|-----:|------:|-----:|------:|
|intercept | -0.39| -0.532| -0.39| -0.532|
'data.frame': 80 obs. of 18 variables:
$ fam : int 1 2 3 4 5 6 7 8 9 10 ...
$ age : int 21 24 21 21 19 26 23 29 24 28 ...
$ zyg : int 1 1 1 1 1 1 1 1 1 1 ...
$ part : int 2 2 2 2 2 2 2 2 2 2 ...
$ wt1 : num -0.502 -0.844 -0.758 0.181 -1.185 ...
$ wt2 : num -0.588 -0.929 -1.185 1.035 -1.356 ...
$ ht1 : num 1.7 1.63 1.65 1.57 1.61 ...
$ ht2 : num 1.7 1.63 1.68 1.65 1.63 ...
$ htwt1 : num 20.1 20.3 20.2 26.8 19.3 ...
$ htwt2 : num 19.7 19.9 17.7 27.9 18.1 ...
$ bmi1 : num 21 21.1 21 23 20.7 ...
$ bmi2 : num 20.9 21 20.1 23.3 20.3 ...
$ cohort : chr "younger" "younger" "younger" "younger" ...
$ zygosity: Factor w/ 5 levels "MZFF","MZMM",..: 1 1 1 1 1 1 1 1 1 1 ...
$ age1 : int 21 24 21 21 19 26 23 29 24 28 ...
$ age2 : int 21 24 21 21 19 26 23 29 24 28 ...
$ obese1 : Ord.factor w/ 3 levels "normal"<"overweight"<..: 2 2 2 3 1 3 2 1 1 3 ...
$ obese2 : Ord.factor w/ 3 levels "normal"<"overweight"<..: 1 1 1 3 1 3 2 1 1 2 ...
Table: Standardized parameter estimates from a 2-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|a2 | c1|c2 | e1|e2 |
|:-----|----:|:----|----:|:--|----:|:----|
|wt | 0.87| | 0.06| | 0.48| |
|obese | 0.63|0.52 | 0.25|. | 0.40|0.33 |
Table: Means (from model$top$expMean)
| | wt1|obese1 | wt2|obese2 |
|:---------|------:|:------|------:|:------|
|intercept | -0.414|0 | -0.414|0 |
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| | a1|c1 | e1|
|:--|----:|:--|----:|
|wt | 0.87|. | 0.49|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.698| 21.698|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.45|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.305| 21.305|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.45|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.313| 21.313|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.46|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.32| 21.32|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.46|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.329| 21.329|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.89| 0.47|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.34| 21.34|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.47|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.351| 21.351|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.48|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.364| 21.364|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.88| 0.48|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.378| 21.378|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.394| 21.394|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.411| 21.411|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.429| 21.429|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.449| 21.449|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.47| 21.47|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.492| 21.492|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.514| 21.514|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.536| 21.536|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.558| 21.558|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.58| 21.58|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.601| 21.601|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.621| 21.621|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.641| 21.641|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.66| 21.66|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.679| 21.679|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.698| 21.698|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.718| 21.718|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.739| 21.739|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|----:|
|bmi |. | 0.8| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.763| 21.763|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.788| 21.788|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.816| 21.816|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.847| 21.847|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|---:|
|bmi |. | 0.8| 0.6|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 21.88| 21.88|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|---:|----:|
|bmi |. | 0.8| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.914| 21.914|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.949| 21.949|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.985| 21.985|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.019| 22.019|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.051| 22.051|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.081| 22.081|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.58|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.108| 22.108|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.131| 22.131|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.152| 22.152|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 22.17| 22.17|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.83| 0.56|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.185| 22.185|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.197| 22.197|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.208| 22.208|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.54|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.216| 22.216|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.223| 22.223|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.229| 22.229|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.233| 22.233|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.238| 22.238|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.242| 22.242|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.86| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.246| 22.246|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.251| 22.251|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.256| 22.256|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.261| 22.261|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.266| 22.266|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.87| 0.49|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|-----:|-----:|
|intercept | 22.27| 22.27|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.272| 22.272|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|---:|
|bmi |. | 0.87| 0.5|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.272| 22.272|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.268| 22.268|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.86| 0.51|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.259| 22.259|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.52|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.244| 22.244|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.85| 0.53|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.223| 22.223|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.84| 0.55|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.194| 22.194|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.82| 0.57|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.158| 22.158|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.81| 0.59|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.115| 22.115|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.78| 0.62|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.066| 22.066|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.76| 0.66|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 22.015| 22.015|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.72| 0.69|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.961| 21.961|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.68| 0.73|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.909| 21.909|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.63| 0.77|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.859| 21.859|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.58| 0.81|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.814| 21.814|
Table: Standardized parameter estimates from a 1-factor Cholesky ACE model. A: additive genetic; C: common environment; E: unique environment.
| |a1 | c1| e1|
|:---|:--|----:|----:|
|bmi |. | 0.53| 0.85|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.776| 21.776|
polite note: in future, please use report = 'markdown', not file='markdown'. file is for choosing a custom html file when writing to the browser with report= 'html'
Table: Standardized parameter estimates from a 1-factor Direct variance ACE model. A: additive genetic; C: common environment; E: unique environment.
| | A1| C1| E1|
|:---|-----:|------:|-----:|
|bmi | 0.807| -0.063| 0.256|
Table: Means (from model$top$expMean)
| | bmi1| bmi2|
|:---------|------:|------:|
|intercept | 21.649| 21.649|
Table: Parameter loadings for model 'check_model_ex'
| |name | Estimate|SE |type |
|:--|:----------|--------:|:----|:---------------|
|11 |G_with_G | 1.00|0 |Factor Variance |
|1 |G_to_x1 | 0.89|0.02 |Factor loading |
|2 |G_to_x2 | 0.93|0.02 |Factor loading |
|3 |G_to_x3 | 0.94|0.02 |Factor loading |
|4 |G_to_x4 | 0.96|0.02 |Factor loading |
|5 |G_to_x5 | 0.97|0.03 |Factor loading |
|6 |x1_with_x1 | 0.21|0 |Residual |
|7 |x2_with_x2 | 0.13|0 |Residual |
|8 |x3_with_x3 | 0.11|0 |Residual |
|9 |x4_with_x4 | 0.07|0 |Residual |
|10 |x5_with_x5 | 0.05|0 |Residual |
[1] "cyl"
[1] "cylinder"
(Intercept) B = 34.661 [29.452, 39.87], t = 13.609, p < 0.001
cyl B = -1.587 [-3.043, -0.131], t = -2.23, p = 0.034
disp B = -0.021 [-0.042, 0], t = -2.007, p = 0.054
R² = 0.76 (adj = 0.743)(Intercept) B = 53.445 [31.077, 75.814], t = 4.894, p < 0.001
cyl B = -8.367 [-16.359, -0.376], t = -2.145, p = 0.041
I(cyl^2) B = 0.597 [-0.096, 1.291], t = 1.766, p = 0.088
disp B = -0.027 [-0.049, -0.006], t = -2.574, p = 0.016
R² = 0.784 (adj = 0.76)(Intercept) B = 34.661 [31.149, 38.173], t = 19.737, p < 0.001
cyl B = -1.587 [-2.569, -0.606], t = -3.234, p = 0.002
disp B = -0.021 [-0.035, -0.006], t = -2.91, p = 0.005
R² = 0.76 (adj = 0.752)(Intercept) B = 34.661 [29.452, 39.87], t = 13.609, p < 0.001
cyl B = -1.587 [-3.043, -0.131], t = -2.23, p = 0.034
disp B = -0.021 [-0.042, 0], t = -2.007, p = 0.054
R² = 0.76 (adj = 0.743)(Intercept) B = -32.432 [-98.452, 33.589], t = -1.005, p = 0.323
cyl B = 24.515 [6.063, 42.966], t = 2.717, p = 0.011
disp B = 0.119 [-0.147, 0.385], t = 0.915, p = 0.368
R² = 0.702 (adj = 0.681)[ FAIL 1 | WARN 7 | SKIP 27 | PASS 339 ]
══ Skipped tests (27) ══════════════════════════════════════════════════════════
• empty test (27): 'test_poly.r:6:1', 'test_umxBuild_run_modify.r:94:1',
'test_umxBuild_run_modify.r:131:1', 'test_umxBuild_run_modify.r:150:1',
'test_umxBuild_run_modify.r:195:1', 'test_umxCP.r:4:1',
'test_umxFactorScores.r:9:1', 'test_umxFitAndReporting.r:191:1',
'test_umxFitAndReporting.r:205:1', 'test_umxMatrixFree.R:6:1',
'test_umxPath.r:7:1', 'test_umx_ACE_etc.r:6:1', 'test_umx_ACE_etc.r:26:1',
'test_umx_ACE_etc.r:69:2', 'test_umx_ACE_etc.r:118:2',
'test_umx_ACE_etc.r:135:2', 'test_umx_ACE_etc.r:163:2',
'test_umx_ACE_etc.r:185:2', 'test_umx_ACE_etc.r:222:1',
'test_umx_ACE_etc.r:236:1', 'test_umx_ACE_etc.r:248:1',
'test_umx_CLPM.r:6:1', 'test_umx_DOC_etc.r:6:1', 'test_umx_misc.r:54:1',
'test_umx_misc.r:96:1', 'test_umx_misc.r:111:1', 'test_umx_misc.r:161:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_umxPower.r:36:2'): umxPower works ──────────────────────────────
Error in `grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y,
resolveHJust(x$just, x$hjust), resolveVJust(x$just, x$vjust),
x$rot, as.numeric(NA))`: conversion failure on 'Power = 1 - β' in 'mbcsToSbcs': for β (U+03B2)
Backtrace:
▆
1. ├─umx::umxPower(m1, "X_with_Y", explore = TRUE) at test_umxPower.r:36:9
2. │ ├─base::print(p)
3. │ ├─base::print(p)
4. │ └─ggplot2:::print.ggplot(p)
5. │ ├─grid::grid.draw(gtable)
6. │ └─grid:::grid.draw.gTree(gtable)
7. │ └─grDevices::recordGraphics(drawGTree(x), list(x = x), getNamespace("grid"))
8. ├─grid:::drawGTree(x)
9. │ ├─grid:::preDraw(x)
10. │ └─grid:::preDraw.gTree(x)
11. │ └─grid:::pushvpgp(x)
12. │ ├─grid:::pushgrobvp(x$vp)
13. │ └─grid:::pushgrobvp.viewport(x$vp)
14. │ └─grid::pushViewport(vp, recording = FALSE)
15. │ └─base::lapply(vps, push.vp, recording)
16. │ ├─grid (local) FUN(X[[i]], ...)
17. │ └─grid:::push.vp.viewport(X[[i]], ...)
18. │ └─grid:::grid.Call.graphics(C_setviewport, vp, TRUE)
19. ├─grid (local) `<fn>`(`<titleGrb>`)
20. ├─grid:::preDraw.gTree(`<titleGrb>`)
21. │ └─grid:::pushvpgp(x)
22. │ ├─grid:::pushgrobvp(x$vp)
23. │ └─grid:::pushgrobvp.viewport(x$vp)
24. │ └─grid::pushViewport(vp, recording = FALSE)
25. │ └─base::lapply(vps, push.vp, recording)
26. │ ├─grid (local) FUN(X[[i]], ...)
27. │ └─grid:::push.vp.vpTree(X[[i]], ...)
28. │ ├─grid:::push.vp(vp$parent, recording)
29. │ └─grid:::push.vp.viewport(vp$parent, recording)
30. │ └─grid:::grid.Call.graphics(C_setviewport, vp, TRUE)
31. └─grid (local) `<fn>`(`<text>`)
32. ├─grid::widthDetails(x)
33. └─grid:::widthDetails.text(x)
34. └─grid:::grid.Call(...)
[ FAIL 1 | WARN 7 | SKIP 27 | PASS 339 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc