A B C D F G H I K L M N P Q R S T V W X Y misc
as.mira | Multiply Imputed Repeated Analyses |
boys | Growth of Dutch boys |
bwplot | Box-and-whisker plot, stripplot, density plot and scatterplot for imputed data |
bwplot.mids | Box-and-whisker plot, stripplot, density plot and scatterplot for imputed data |
cbind.mids | Combine a Multiply Imputed Data Set with other mids object or dataframe |
cc | Extracts complete and incomplete cases |
cc-method | Extracts complete and incomplete cases |
cci | Extracts (in)complete case indicator |
cci-method | Extracts (in)complete case indicator |
ccn | Number of (in)complete cases |
ccn-method | Number of (in)complete cases |
complete | Creates a Complete Flat File from a Multiply Imputed Data Set |
densityplot | Box-and-whisker plot, stripplot, density plot and scatterplot for imputed data |
densityplot.mids | Box-and-whisker plot, stripplot, density plot and scatterplot for imputed data |
fdd | SE Fireworks Disaster Data |
fdd.pred | SE Fireworks Disaster Data |
fdgs | Fifth Dutch Growth Study 2009 |
fico | Influx and outflux of multivatiate missing data patterns |
fireworks | SE Fireworks Disaster Data |
flux | Influx and outflux of multivatiate missing data patterns |
fluxplot | Influx and outflux of multivatiate missing data patterns |
getfit | Extracts fit objects from mira object |
glm.mids | Generalized Linear Model for Multiply Imputed Data |
growth | Fifth Dutch Growth Study 2009 |
hazard | Cumulative hazard rate or Nelson-Aalen estimator |
ibind | Combine imputations fitted to the same data |
ic | Extracts complete and incomplete cases |
ic-method | Extracts complete and incomplete cases |
ici | Extracts (in)complete case indicator |
ici-method | Extracts (in)complete case indicator |
icn | Number of (in)complete cases |
icn-method | Number of (in)complete cases |
is.mids | Multiply Imputed Data Set |
is.mipo | Multiply Imputed Pooled Analysis |
is.mira | Multiply Imputed Repeated Analyses |
krul | Self-reported and measured BMI |
leiden85 | Leiden 85+ Study |
lm.mids | Linear Regression on Multiply Imputed Data |
logreg | Multiple Imputation by Logistic Regression |
logreg.boot | Multiple Imputation by Logistic Regression |
mammalsleep | Mammal sleep data |
md.pairs | Missing data pattern by variable pairs |
md.pattern | Missing Data Pattern |
mdc | Graphical parameter for missing data plots. |
mgg | Self-reported and measured BMI |
mice | Multivariate Imputation by Chained Equations (MICE) |
mice.impute.2L.norm | Imputation by a Two-Level Normal Model |
mice.impute.2l.norm | Imputation by a Two-Level Normal Model |
mice.impute.2L.pan | Imputation by a Two-Level Normal Model using pan |
mice.impute.2l.pan | Imputation by a Two-Level Normal Model using pan |
mice.impute.2lonly.mean | Imputation of the mean within the class |
mice.impute.2lonly.norm | Imputation at Level 2 by Bayesian Linear Regression |
mice.impute.2lonly.pmm | Imputation at Level 2 by Predictive Mean Matching |
mice.impute.lda | Imputation by Linear Discriminant Analysis |
mice.impute.logreg | Multiple Imputation by Logistic Regression |
mice.impute.logreg.boot | Multiple Imputation by Logistic Regression |
mice.impute.mean | Imputation by the Mean |
mice.impute.norm | Imputation by Bayesian Linear Regression |
mice.impute.norm.boot | Imputation by Linear Regression, Bootstrap Method |
mice.impute.norm.nob | Imputation by Linear Regression (non Bayesian) |
mice.impute.norm.predict | Imputation by Linear Regression, Prediction Method |
mice.impute.passive | Passive Imputation |
mice.impute.pmm | Imputation by Predictive Mean Matching |
mice.impute.pmm2 | Imputation by Predictive Mean Matching |
mice.impute.polr | Imputation by Polytomous Regression |
mice.impute.polyreg | Imputation by Polytomous Regression |
mice.impute.quadratic | Imputation of quadratric terms |
mice.impute.sample | Imputation by Simple Random Sampling |
mice.mids | Multivariate Imputation by Chained Equations (Iteration Step) |
mice.theme | Graphical parameter for missing data plots. |
mids | Multiply Imputed Data Set |
mids-class | Multiply Imputed Data Set |
mids2mplus | Export Multiply Imputed Data to Mplus |
mids2spss | Export Multiply Imputed Data to SPSS |
mipo | Multiply Imputed Pooled Analysis |
mipo-class | Multiply Imputed Pooled Analysis |
mira | Multiply Imputed Repeated Analyses |
mira-class | Multiply Imputed Repeated Analyses |
nelsonaalen | Cumulative hazard rate or Nelson-Aalen estimator |
nhanes | NHANES example - all variables numerical |
nhanes2 | NHANES example - mixed numerical and discrete variables |
norm | Imputation by Bayesian Linear Regression |
norm.boot | Imputation by Linear Regression, Bootstrap Method |
norm.nob | Imputation by Linear Regression (non Bayesian) |
norm.predict | Imputation by Linear Regression, Prediction Method |
pattern1 | Datasets with various missing data patterns |
pattern2 | Datasets with various missing data patterns |
pattern3 | Datasets with various missing data patterns |
pattern4 | Datasets with various missing data patterns |
plot | Multiply Imputed Data Set |
plot-method | Multiply Imputed Data Set |
plot.mids | Multiply Imputed Data Set |
pmm | Imputation by Predictive Mean Matching |
pmm2 | Imputation by Predictive Mean Matching |
pool | Multiple Imputation Pooling |
pool.compare | Compare two nested models fitted to imputed data |
pool.r.squared | Pooling: R squared |
pool.scalar | Multiple Imputation Pooling: Univariate version |
popmis | Hox pupil popularity data with missing popularity scores |
pops | Project On Preterm and Small for Gestational Age Infants (POPS) |
pops.pred | Project On Preterm and Small for Gestational Age Infants (POPS) |
potthoffroy | Potthoff-Roy data |
print-method | Multiply Imputed Data Set |
print-method | Multiply Imputed Pooled Analysis |
print-method | Multiply Imputed Repeated Analyses |
quadratic | Imputation of quadratric terms |
quickpred | Quick selection of predictors from the data |
rbind.mids | Combine a Multiply Imputed Data Set with other mids object or dataframe |
selfreport | Self-reported and measured BMI |
sleep | Mammal sleep data |
stripplot | Box-and-whisker plot, stripplot, density plot and scatterplot for imputed data |
stripplot.mids | Box-and-whisker plot, stripplot, density plot and scatterplot for imputed data |
summary-method | Multiply Imputed Data Set |
summary-method | Multiply Imputed Pooled Analysis |
summary-method | Multiply Imputed Repeated Analyses |
supports.transparent | Does the current graphic device support semi-transparent foreground colors? |
tbc | Terneuzen Birth Cohort |
tbc.target | Terneuzen Birth Cohort |
terneuzen | Terneuzen Birth Cohort |
transparent | Does the current graphic device support semi-transparent foreground colors? |
version | Echoes the package version number |
walking | Walking disability data |
windspeed | Subset of Irish wind speed data |
with.mids | Evaluate an expression in multiple imputed datasets |
xyplot | Box-and-whisker plot, stripplot, density plot and scatterplot for imputed data |
xyplot.mids | Box-and-whisker plot, stripplot, density plot and scatterplot for imputed data |
YA | Walking disability data |
YB | Walking disability data |
2L.norm | Imputation by a Two-Level Normal Model |
2L.pan | Imputation by a Two-Level Normal Model using pan |
2l.pan | Imputation by a Two-Level Normal Model using pan |
2lonly.mean | Imputation of the mean within the class |
2lonly.norm | Imputation at Level 2 by Bayesian Linear Regression |
2lonly.pmm | Imputation at Level 2 by Predictive Mean Matching |