⚠️There's a newer version (3.17.0) of this package.Take me there.

mice (version 2.1)

Multivariate Imputation by Chained Equations

Description

Multiple Imputation using Fully Conditional Specification

Copy Link

Version

Install

install.packages('mice')

Monthly Downloads

83,091

Version

2.1

License

GPL-2 | GPL-3

Maintainer

Stef van Buuren

Last Published

September 18th, 2009

Functions in mice (2.1)

mice.impute.sample

Imputation by Simple Random Sampling

mice.internal

Internal mice functions

mice.impute.mean

Imputation by the Mean

md.pattern

Missing Data Pattern

mids

Multiply Imputed Data Set

mipo

Multiply Imputed Pooled Analysis

mice.impute.polyreg

Imputation by Polytomous Regression

mice.impute.passive

Passive Imputation

getfit

Extracts fit objects from mira object

mice.mids

Multivariate Imputation by Chained Equations (Iteration Step)

with.mids

Evaluate an expression in multiple imputed datasets

lm.mids

Linear Regression on Multiply Imputed Data

version

Echoes the package version number

complete

Creates a Complete Flat File from a Multiply Imputed Data Set

nelsonaalen

Cumulative hazard rate or Nelson-Aalen estimator

ccn

Number of (in)complete cases

mids2mplus

Export Multiply Imputed Data to Mplus

mice.impute.pmm

Imputation by Predictive Mean Matching

nhanes

NHANES example - all variables numerical

nhanes2

NHANES example - mixed numerical and discrete variables

mids2spss

Export Multiply Imputed Data to SPSS

mira

Multiply Imputed Repeated Analyses

mice

Multivariate Imputation by Chained Equations (MICE)

cci

Extracts (in)complete case indicator

mice.impute.norm.predict

Imputation by Linear Regression, Prediction Method

mice.impute.lda

Imputation by Linear Discriminant Analysis

stripplot

Box-and-whisker plot, stripplot, density plot and scatterplot for imputed data

mice.impute.logreg

Multiple Imputation by Logistic Regression

Extracts complete and incomplete cases

pool.r.squared

Pooling: R squared

pool

Multiple Imputation Pooling

md.pairs

Missing data pattern by variable pairs

mdc

Graphical parameter for missing data plots.

quickpred

Quick selection of predictors from the data

glm.mids

Generalized Linear Model for Multiply Imputed Data

mice.impute.norm.boot

Imputation by Linear Regression, Bootstrap Method

mice.impute.quadratic

Imputation of quadratric terms

mice.auxiliary

Auxiliary functions used in FIMD

mice.impute.2l.pan

Imputation by a two-level normal model using pan

fdgs

Fifth Dutch growth study 2009

mice.impute.2lonly.pmm

Imputation at Level 2 by Predictive Mean Matching

supports.transparent

Does the current graphic device support semi-transparent foreground colors?

fdd

SE Fireworks disaster data

mice.impute.cart

Imputation by classification and regression trees

flux

Influx and outflux of multivatiate missing data patterns

ifdo

Conditional imputation helper

Extract broken stick estimates from a lmer object

summary.mira

Summary of a mira object

Incomplete cases

stripplot.mids

Stripplot of observed and imputed data

bwplot.mids

Box-and-whisker plot of observed and imputed data

leiden85

Leiden 85+ study

ici

Incomplete case indicator

mids-class

Multiply imputed data set (mids)

fluxplot

Fluxplot of the missing data pattern

densityplot.mids

Density plot of observed and imputed data

mice.impute.norm.nob

Imputation by linear regression (non Bayesian)

as.mira

Create a mira object from repeated analyses

mice.impute.norm

Imputation by Bayesian linear regression

rbind.mids

Rowwise combination of a mids object.

boys

Growth of Dutch boys

fico

Fraction of incomplete cases among cases with observed

mice.impute.2lonly.norm

Imputation at level 2 by Bayesian linear regression

mipo-class

Multiply imputed pooled analysis (mipo)

pool.compare

Compare two nested models fitted to imputed data

xyplot.mids

Scatterplot of observed and imputed data

squeeze

Squeeze the imputed values to be within specified boundaries.

pool.scalar

Multiple imputation pooling: univariate version

mice.impute.2l.norm

Imputation by a two-level normal model

pops

Project on preterm and small for gestational age infants (POPS)

tbc

Terneuzen birth cohort

mice.impute.polr

Imputation by polytomous regression - ordered

long2mids

Conversion of a imputed data set (long form) to a mids object

popmis

Hox pupil popularity data with missing popularity scores

ibind

Combine imputations fitted to the same data

mice.theme

Set the theme for the plotting Trellis functions

plot.mids

Plot the trace lines of the MICE algorithm

appendbreak

Appends specified break to the data

as.mids

Converts an multiply imputed dataset (long format) into a mids object

pattern

Datasets with various missing data patterns

selfreport

Self-reported and measured BMI

.pmm.match

Finds an imputed value from matches in the predictive metric

mira-class

Multiply imputed repeated analyses (mira)

is.mira

Check for mira object

print.mids

Print a mids object

is.mipo

Check for mipo object

mice.impute.2lonly.mean

Imputation of the mean within the class

cbind.mids

Columnwise combination of a mids object.

mice.impute.ri

Imputation by the random indicator method for nonignorable data

windspeed

Subset of Irish wind speed data

walking

Walking disability data

is.mids

Check for mids object

.norm.draw

Draws values of beta and sigma by Bayesian linear regression

potthoffroy

Potthoff-Roy data

mice.impute.logreg.boot

Imputation by logistic regression using the bootstrap