## Not run:
# #############################################################################
# # EXAMPLE 1: Nested multiple imputation and conversion into an object of class
# # NestedImputationList
# #############################################################################
#
# 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) ]
# }
#
# # nested multiple imputation using mice
# imp1 <- mice.nmi( datlist , m=3 , maxit=2 )
# summary(imp1)
#
# # create object of class NestedImputationList
# datlist1 <- mids2datlist( imp1 )
# datlist1 <- NestedImputationList( datlist1 )
#
# # estimate linear model using with
# res1 <- with( datlist1 , stats::lm( ASMMAT ~ female + migrant ) )
# # pool results
# mres1 <- mitools::MIcombine( res1 )
# summary(mres1)
# coef(mres1)
# vcov(mres1)
# ## End(Not run)
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