Multivariate Imputation by Chained Equations


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Documentation for package ‘mice’ version 2.25

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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