2L.norm |
Imputation by a Two-Level Normal Model |
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 |
glm.mids |
Generalized Linear Model for Multiply Imputed Data |
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 |
lm.mids |
Linear Regression on Multiply Imputed Data |
logreg |
Multiple Imputation by Logistic Regression |
logreg.boot |
Multiple Imputation by Logistic Regression |
md.pairs |
Missing data pattern by variable pairs |
md.pattern |
Missing Data Pattern |
mdc |
Graphical parameter for missing data plots. |
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.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.polr |
Imputation by Polytomous Regression |
mice.impute.polyreg |
Imputation by Polytomous Regression |
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 |
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 |
plot |
Multiply Imputed Data Set |
plot-method |
Multiply Imputed Data Set |
plot.mids |
Multiply Imputed Data Set |
pmm |
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 |
print-method |
Multiply Imputed Data Set |
print-method |
Multiply Imputed Pooled Analysis |
print-method |
Multiply Imputed Repeated Analyses |
quickpred |
Quick selection of predictors from the data |
rbind.mids |
Combine a Multiply Imputed Data Set with other mids object or dataframe |
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 |
version |
Echoes the package version number |
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 |