Man pages for mice
Multivariate Imputation by Chained Equations

amputeGenerate missing data for simulation purposes
ampute.continuousMultivariate amputation based on continuous probability...
ampute.default.freqDefault 'freq' in 'ampute'
ampute.default.oddsDefault 'odds' in 'ampute()'
ampute.default.patternsDefault 'patterns' in 'ampute'
ampute.default.typeDefault 'type' in 'ampute()'
ampute.default.weightsDefault 'weights' in 'ampute'
ampute.discreteMultivariate amputation based on discrete probability...
ampute.mcarMultivariate amputation under a MCAR mechanism
anovaCompare several nested models
appendbreakAppends specified break to the data
as.midsConverts an imputed dataset (long format) into a 'mids'...
as.miraCreate a 'mira' object from repeated analyses
as.mitml.resultConverts into a 'mitml.result' object
boysGrowth of Dutch boys
brandsmaBrandsma school data used Snijders and Bosker (2012)
bwplot.madsBox-and-whisker plot of amputed and non-amputed data
bwplot.midsBox-and-whisker plot of observed and imputed data
cbindCombine R objects by rows and columns
ccSelect complete cases
cciComplete case indicator
complete.midsExtracts the completed data from a 'mids' object
construct.blocksConstruct blocks from 'formulas' and 'predictorMatrix'
convergenceComputes convergence diagnostics for a 'mids' object
D1Compare two nested models using D1-statistic
D2Compare two nested models using D2-statistic
D3Compare two nested models using D3-statistic
densityplot.midsDensity plot of observed and imputed data
employeeEmployee selection data
estimiceComputes least squares parameters
extend.formulaExtends a formula with predictors
extend.formulasExtends formula's with predictor matrix settings
extractBSExtract broken stick estimates from a 'lmer' object
fddSE Fireworks disaster data
fdgsFifth Dutch growth study 2009
ficoFraction of incomplete cases among cases with observed
filter.midsSubset rows of a 'mids' object
fix.coefFix coefficients and update model
fluxInflux and outflux of multivariate missing data patterns
fluxplotFluxplot of the missing data pattern
futuremiceWrapper function that runs MICE in parallel
getfitExtract list of fitted models
getqbarExtract estimate from 'mipo' object
glance.mipoGlance method to extract information from a 'mipo' object
glm.midsGeneralized linear model for 'mids' object
ibindEnlarge number of imputations by combining 'mids' objects
icSelect incomplete cases
iciIncomplete case indicator
ifdoConditional imputation helper
is.madsCheck for 'mads' object
is.midsCheck for 'mids' object
is.mipoCheck for 'mipo' object
is.miraCheck for 'mira' object
is.mitml.resultCheck for 'mitml.result' object
leiden85Leiden 85+ study
lm.midsLinear regression for 'mids' object
mads-classMultivariate amputed data set ('mads')
make.blocksCreates a 'blocks' argument
make.blotsCreates a 'blots' argument
make.formulasCreates a 'formulas' argument
make.methodCreates a 'method' argument
make.postCreates a 'post' argument
make.predictorMatrixCreates a 'predictorMatrix' argument
make.visitSequenceCreates a 'visitSequence' argument
make.whereCreates a 'where' argument
mammalsleepMammal sleep data
matchindexFind index of matched donor units
mcarJamshidian and Jalal's Non-Parametric MCAR Test
mdcGraphical parameter for missing data plots
md.pairsMissing data pattern by variable pairs
md.patternMissing data pattern
mice'mice': Multivariate Imputation by Chained Equations
mice.impute.2l.binImputation by a two-level logistic model using 'glmer'
mice.impute.2l.lmerImputation by a two-level normal model using 'lmer'
mice.impute.2l.normImputation by a two-level normal model
mice.impute.2lonly.meanImputation of most likely value within the class
mice.impute.2lonly.normImputation at level 2 by Bayesian linear regression
mice.impute.2lonly.pmmImputation at level 2 by predictive mean matching
mice.impute.2l.panImputation by a two-level normal model using 'pan'
mice.impute.cartImputation by classification and regression trees
mice.impute.jomoImputeMultivariate multilevel imputation using 'jomo'
mice.impute.lasso.logregImputation by direct use of lasso logistic regression
mice.impute.lasso.normImputation by direct use of lasso linear regression by indirect use of lasso logistic regression by indirect use of lasso linear regression
mice.impute.ldaImputation by linear discriminant analysis
mice.impute.logregImputation by logistic regression
mice.impute.logreg.bootImputation by logistic regression using the bootstrap
mice.impute.meanImputation by the mean
mice.impute.midastouchImputation by predictive mean matching with distance aided...
mice.impute.mnarImputation under MNAR mechanism by NARFCS
mice.impute.mpmmImputation by multivariate predictive mean matching
mice.impute.normImputation by Bayesian linear regression
mice.impute.norm.bootImputation by linear regression, bootstrap method
mice.impute.norm.nobImputation by linear regression without parameter uncertainty
mice.impute.norm.predictImputation by linear regression through prediction
mice.impute.panImputeImpute multilevel missing data using 'pan'
mice.impute.passivePassive imputation
mice.impute.pmmImputation by predictive mean matching
mice.impute.polrImputation of ordered data by polytomous regression
mice.impute.polyregImputation of unordered data by polytomous regression
mice.impute.quadraticImputation of quadratic terms
mice.impute.rfImputation by random forests
mice.impute.riImputation by the random indicator method for nonignorable...
mice.impute.sampleImputation by simple random sampling
mice.midsMultivariate Imputation by Chained Equations (Iteration Step)
mice.themeSet the theme for the plotting Trellis functions
mids2mplusExport 'mids' object to Mplus
mids2spssExport 'mids' object to SPSS
mids-classMultiply imputed data set ('mids')
mipo'mipo': Multiple imputation pooled object
mira-classMultiply imputed repeated analyses ('mira')
mnar_demo_dataMNAR demo data
name.blocksName imputation blocks
name.formulasName formula list elements
nccNumber of complete cases
nelsonaalenCumulative hazard rate or Nelson-Aalen estimator
nhanesNHANES example - all variables numerical
nhanes2NHANES example - mixed numerical and discrete variables
nicNumber of incomplete cases
nimpNumber of imputations per block
norm.drawDraws values of beta and sigma by Bayesian linear regression
parlmiceWrapper function that runs MICE in parallel
patternDatasets with various missing data patterns
plot.midsPlot the trace lines of the MICE algorithm
pmm.matchFinds an imputed value from matches in the predictive metric...
poolCombine estimates by pooling rules
pool.compareCompare two nested models fitted to imputed data
pool.r.squaredPools R^2 of m models fitted to multiply-imputed data
pool.scalarMultiple imputation pooling: univariate version
popmisHox pupil popularity data with missing popularity scores
popsProject on preterm and small for gestational age infants...
potthoffroyPotthoff-Roy data
printPrint a 'mids' object
print.madsPrint a 'mads' object
quickpredQuick selection of predictors from the data
reexportsObjects exported from other packages
selfreportSelf-reported and measured BMI
squeezeSqueeze the imputed values to be within specified boundaries.
stripplot.midsStripplot of observed and imputed data
summarySummary of a 'mira' object
supports.transparentSupports semi-transparent foreground colors?
tbcTerneuzen birth cohort
tidy.mipoTidy method to extract results from a 'mipo' object
toenailToenail data
toenail2Toenail data
versionEchoes the package version number
walkingWalking disability data
windspeedSubset of Irish wind speed data
with.midsEvaluate an expression in multiple imputed datasets
xyplot.madsScatterplot of amputed and non-amputed data against weighted...
xyplot.midsScatterplot of observed and imputed data
mice documentation built on June 7, 2023, 5:38 p.m.