miceadds (version 1.6-0)

mids2datlist: Converting a mids, mids.1chain or mids.nmi Object in a Dataset List

Description

Converts a mids, mids.1chain or mids.nmi object in a dataset list.

Usage

mids2datlist(midsobj, X = NULL)

Arguments

midsobj

Object of class mids, mids.1chain or mids.nmi

X

Optional data frame of variables to be included in imputed datasets.

Value

• List of multiply imputed datasets of classes datlist or nested.datlist.

Examples

#############################################################################
# EXAMPLE 1: Imputing nhanes data and convert result into a dataset list
#############################################################################

data(nhanes,package="mice")

#**** imputation using mice
imp1 <- mice::mice( nhanes , m=3 , maxit=5 )
# convert mids object into list
datlist1 <- mids2datlist( imp1 )

#**** imputation using mice.1chain
imp2 <- mice.1chain( nhanes , burnin=4 , iter=20 , Nimp=5 )
# convert mids.1chain object into list
datlist2 <- mids2datlist( imp2 )

#############################################################################
# EXAMPLE 2: Nested multiple imputation and datalist conversion
#############################################################################

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

# remove first four variables
M <- length(datlist)
for (ll in 1:M){
    datlist[[ll]] <- datlist[[ll]][ , -c(1:4) ]
                }
                
#***************
# (1) nested multiple imputation using mice
imp1 <- mice.nmi( datlist ,  m=4 , maxit=3 )
summary(imp1)

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

#**************
# conversion into a datalist
datlist.i1 <- mids2datlist( imp1 )
datlist.i2 <- mids2datlist( imp2 )

#############################################################################
# EXAMPLE 3: mids object conversion and inclusion of further variables
#############################################################################

data(data.ma05)
dat <- data.ma05

# imputation
resp <- dat[ , - c(1:2) ]
imp <- mice::mice( resp , imputationMethod="norm" , maxit=2 , m=3 )

# convert mids object into datalist
datlist0 <- mids2datlist( imp )
# convert mids object into datalist and include some id variables
datlist1 <- mids2datlist( imp , X = dat[,c(1,2) ] )