miceadds: mice.nmi – R documentation

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mice.nmi

Nested Multiple Imputation

Description

Performs nested multiple imputation (Rubin, 2003) for the functions mice::mice and mice.1chain. The function mice.nmi generates an object of class mids.nmi.

Usage

mice.nmi(datlist, type="mice", ...)

## S3 method for class 'mids.nmi'
summary(object, ...)

## S3 method for class 'mids.nmi'
print(x, ...)

Arguments

`datlist`	List of datasets for which nested multiple imputation should be applied
`type`	Imputation model: `type="mice"` for `mice::mice` or `type="mice.1chain"` for `mice.1chain`.
`...`	Arguments to be passed to `mice::mice` or `mice.1chain`.
`object`	Object of class `mids.nmi`.
`x`	Object of class `mids.nmi`.

Value

Object of class mids.nmi with entries

`imp`	List of nested multiply imputed datasets whose entries are of class `mids` or `mids.1chain`.
`Nimp`	Number of between and within imputations.

References

Rubin, D. B. (2003). Nested multiple imputation of NMES via partially incompatible MCMC. Statistica Neerlandica, 57(1), 3-18. doi: 10.1111/1467-9574.00217

Examples

## Not run: 
#############################################################################
# EXAMPLE 1: Nested multiple imputation for TIMSS data
#############################################################################

library(BIFIEsurvey)
data(data.timss2, package="BIFIEsurvey" )
datlist <- data.timss2
   # list of 5 datasets containing 5 plausible values

#** define imputation method and predictor matrix
data <- datlist[[1]]
V <- ncol(data)
# variables
vars <- colnames(data)
# variables not used for imputation
vars_unused <- miceadds::scan.vec("IDSTUD TOTWGT  JKZONE  JKREP" )

#- define imputation method
impMethod <- rep("norm", V )
names(impMethod) <- vars
impMethod[ vars_unused ] <- ""

#- define predictor matrix
predM <- matrix( 1, V, V )
colnames(predM) <- rownames(predM) <- vars
diag(predM) <- 0
predM[, vars_unused ] <- 0

#***************
# (1) nested multiple imputation using mice
imp1 <- miceadds::mice.nmi( datlist, method=impMethod, predictorMatrix=predM,
                m=4, maxit=3 )
summary(imp1)

#***************
# (2) nested multiple imputation using mice.1chain
imp2 <- miceadds::mice.nmi( datlist, method=impMethod, predictorMatrix=predM,
            Nimp=4, burnin=10,iter=22, type="mice.1chain")
summary(imp2)

## End(Not run)

miceadds

Some Additional Multiple Imputation Functions, Especially for 'mice'

v3.11-6

GPL (>= 2)

Authors

Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>), Simon Grund [aut] (<https://orcid.org/0000-0002-1290-8986>), Thorsten Henke [ctb]

Initial release

2021-01-21 11:48:47