complete.mids.nmi( x, action=c(1,1) )

complete.mids.1chain( x, action=1 )

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

library(BIFIEsurvey)
data(data.timss2, package="BIFIEsurvey" )
datlist <- data.timss2

# 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 <- miceadds::mice.nmi( datlist,  m=4, maxit=3 )
summary(imp1)

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

#**************
# extract dataset for third orginal dataset the second within imputation
dat32a <- miceadds::complete.mids.nmi( imp1, action=c(3,2) )
dat32b <- miceadds::complete.mids.nmi( imp2, action=c(3,2) )

#############################################################################
# EXAMPLE 2: Imputation from one chain and extracting dataset for nhanes data
#############################################################################

library(mice)
data(nhanes, package="mice")

# nhanes data in one chain
imp1 <- miceadds::mice.1chain( nhanes, burnin=5, iter=40, Nimp=4,
            method=rep("norm", 4 ) )

# extract first imputed dataset
dati1 <- miceadds::complete.mids.1chain( imp1, action=1 )

## End(Not run)