metacont {meta} | R Documentation |
Calculation of fixed and random effects estimates for meta-analyses with continuous outcome data; inverse variance weighting is used for pooling.
metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c, studlab, data=NULL, subset=NULL, sm="MD", level = 0.95, level.comb = level, comb.fixed=TRUE, comb.random=TRUE, title="", complab="", outclab="", label.e="Experimental", label.c="Control", byvar, bylab, print.byvar=TRUE)
n.e |
Number of observations in experimental group. |
mean.e |
Estimated mean in experimental group. |
sd.e |
Standard deviation in experimental group. |
n.c |
Number of observations in control group. |
mean.c |
Estimated mean in control group. |
sd.c |
Standard deviation in control group. |
studlab |
An optional vector with study labels. |
data |
An optional data frame containing the study information. |
subset |
An optional vector specifying a subset of studies to be used. |
level |
The level used to calculate confidence intervals for individual studies. |
level.comb |
The level used to calculate confidence intervals for pooled estimates. |
comb.fixed |
A logical indicating whether a fixed effect meta-analysis should be conducted. |
comb.random |
A logical indicating whether a random effects meta-analysis should be conducted. |
title |
Title of meta-analysis / systematic review. |
complab |
Comparison label. |
outclab |
Outcome label. |
label.e |
Label for experimental group. |
label.c |
Label for control group. |
sm |
A character string indicating which summary measure
("MD" or "SMD" ) is to be used for pooling of
studies. |
byvar |
An optional vector containing grouping information (must
be of same length as n.e ). |
bylab |
A character string with a label for the grouping variable. |
print.byvar |
A logical indicating whether the name of the grouping variable should be printed in front of the group labels. |
Calculation of fixed and random effects estimates for meta-analyses
with continuous outcome data; inverse variance weighting is used for
pooling. The DerSimonian-Laird estimate is used in the
random effects model. The mean difference is used as measure of
treatment effect if sm="MD"
– which correspond to
sm="WMD"
in older versions (<0.9) of the meta package. For the
summary measure "SMD"
, Hedges' adjusted g is utilised for
pooling.
Internally, both fixed effect and random effects models are calculated
regardless of values choosen for arguments comb.fixed
and
comb.random
. Accordingly, the estimate for the random effects
model can be extracted from component TE.random
of an object
of class "meta"
even if comb.random=FALSE
. However, all
functions in R package meta
will adequately consider the values
for comb.fixed
and comb.random
. E.g. function
print.meta
will not print results for the random effects
model if comb.random=FALSE
.
The function metagen
is called internally to calculate
individual and overall treatment estimates and standard errors.
An object of class c("metacont", "meta")
with corresponding
print
, summary
, plot
function. The object is a
list containing the following components:
n.e, mean.e, sd.e, |
|
n.c, mean.c, sd.c, |
|
studlab, sm, level, level.comb, |
|
comb.fixed, comb.random, |
|
byvar, bylab, print.byvar |
As defined above. |
TE, seTE |
Estimated treatment effect and standard error of individual studies. |
w.fixed, w.random |
Weight of individual studies (in fixed and random effects model). |
TE.fixed, seTE.fixed |
Estimated overall treatment effect and standard error (fixed effect model). |
TE.random, seTE.random |
Estimated overall treatment effect and standard error (random effects model). |
k |
Number of studies combined in meta-analysis. |
Q |
Heterogeneity statistic. |
tau |
Square-root of between-study variance (moment estimator of DerSimonian-Laird). |
method |
Pooling method: "Inverse" . |
call |
Function call. |
Guido Schwarzer sc@imbi.uni-freiburg.de
Cooper H & Hedges LV (1994), The Handbook of Research Synthesis. Newbury Park, CA: Russell Sage Foundation.
data(Fleiss93cont) meta1 <- metacont(n.e, mean.e, sd.e, n.c, mean.c, sd.c, data=Fleiss93cont, sm="SMD") meta1 meta2 <- metacont(Fleiss93cont$n.e, Fleiss93cont$mean.e, Fleiss93cont$sd.e, Fleiss93cont$n.c, Fleiss93cont$mean.c, Fleiss93cont$sd.c, sm="SMD") meta2