# Multivariate Imputation by Chained Equations

## Documentation for package ‘mice’ version 2.25

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

A B C D E F G H I L M N P Q R S T V W X misc

## -- A --

appendbreak | Appends specified break to the data
as.mids | Converts an multiply imputed dataset (long format) into a 'mids' object
as.mira | Create a 'mira' object from repeated analyses

## -- B --

boys | Growth of Dutch boys
bwplot | Box-and-whisker plot of observed and imputed data
bwplot.mids | Box-and-whisker plot of observed and imputed data

## -- C --

cart | Imputation by classification and regression trees
cbind.mids | Columnwise combination of a 'mids' object.
cc | Complete cases
cc-method | Complete cases
cci | Complete case indicator
cci-method | Complete case indicator
ccn | Complete cases n
ccn-method | Complete cases n
complete | Creates imputed data sets from a 'mids' object

## -- D --

densityplot | Density plot of observed and imputed data
densityplot.mids | Density plot of observed and imputed data

## -- E --

extractBS | Extract broken stick estimates from a 'lmer' object

## -- F --

fastpmm | Imputation by fast predictive mean matching
fdd | SE Fireworks disaster data
fdd.pred | SE Fireworks disaster data
fdgs | Fifth Dutch growth study 2009
fico | Fraction of incomplete cases among cases with observed
flux | Influx and outflux of multivariate missing data patterns
fluxplot | Fluxplot of the missing data pattern

## -- G --

getfit | Extracts fit objects from 'mira' object
glm.mids | Generalized linear model for 'mids' object

## -- H --

hazard | Cumulative hazard rate or Nelson-Aalen estimator

## -- I --

ibind | Combine imputations fitted to the same data
ic | Incomplete cases
ic-method | Incomplete cases
ici | Incomplete case indicator
ici-method | Incomplete case indicator
icn | Incomplete cases n
icn-method | Incomplete cases n
is.mids | Check for 'mids' object
is.mipo | Check for 'mipo' object
is.mira | Check for 'mira' object

## -- L --

leiden85 | Leiden 85+ study
lm.mids | Linear regression for 'mids' object

## -- M --

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.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.cart | Imputation by classification and regression trees
mice.impute.fastpmm | Imputation by fast predictive mean matching
mice.impute.lda | Imputation by linear discriminant analysis
mice.impute.logreg | Imputation by logistic regression
mice.impute.logreg.boot | Imputation by logistic regression using the bootstrap
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 - ordered
mice.impute.polyreg | Imputation by polytomous regression - unordered
mice.impute.quadratic | Imputation of quadratric terms
mice.impute.rf | Imputation by random forests
mice.impute.ri | Imputation by the random indicator method for nonignorable data
mice.impute.sample | Imputation by simple random sampling
mice.mids | Multivariate Imputation by Chained Equations (Iteration Step)
mice.theme | Set the theme for the plotting Trellis functions
mids | Multiply imputed data set ('mids')
mids-class | Multiply imputed data set ('mids')
mids2mplus | Export 'mids' object to Mplus
mids2spss | Export 'mids' object to SPSS
mipo | Multiply imputed pooled analysis ('mipo')
mipo-class | Multiply imputed pooled analysis ('mipo')
mira | Multiply imputed repeated analyses ('mira')
mira-class | Multiply imputed repeated analyses ('mira')

## -- N --

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.draw | Draws values of beta and sigma by Bayesian linear regression
norm.nob | Imputation by linear regression (non Bayesian)
norm.predict | Imputation by linear regression, prediction method

## -- P --

pattern | Datasets with various missing data patterns
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.mids | Plot the trace lines of the MICE algorithm
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
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.mids | Print a 'mids' object
print.mipo | Print a 'mids' object
print.mira | Print a 'mids' object

## -- Q --

quadratic | Imputation of quadratric terms
quickpred | Quick selection of predictors from the data

## -- R --

rbind.mids | Rowwise combination of a 'mids' object.
ri | Imputation by the random indicator method for nonignorable data

## -- S --

selfreport | Self-reported and measured BMI
sleep | Mammal sleep data
squeeze | Squeeze the imputed values to be within specified boundaries.
stripplot | Stripplot of observed and imputed data
stripplot.mids | Stripplot of observed and imputed data
summary.mids | Summary of a 'mira' object
summary.mipo | Summary of a 'mira' object
summary.mira | Summary of a 'mira' object
supports.transparent | Supports semi-transparent foreground colors?

## -- T --

tbc | Terneuzen birth cohort
tbc.target | Terneuzen birth cohort
terneuzen | Terneuzen birth cohort
transparent | Supports semi-transparent foreground colors?

## -- V --

version | Echoes the package version number

## -- W --

walking | Walking disability data
windspeed | Subset of Irish wind speed data
with.mids | Evaluate an expression in multiple imputed datasets

## -- X --

xyplot | Scatterplot of observed and imputed data
xyplot.mids | Scatterplot of observed and imputed data

## -- misc --

.norm.draw | Draws values of beta and sigma by Bayesian linear regression
2l.norm | Imputation by a two-level normal model
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