Conversion of a BIFIEdata Object into a svyrep Object in the survey Package (and the other way around)

The function BIFIEdata2svrepdesign converts of a BIFIEdata object into a svyrep object in the survey package.

The function svrepdesign2BIFIEdata converts a svyrep object in the survey package into an object of class BIFIEdata.

BIFIEdata2svrepdesign(bifieobj, varnames=NULL, impdata.index=NULL)

svrepdesign2BIFIEdata(svrepdesign, varnames=NULL, cdata=FALSE)

Arguments

bifieobj

Object of class BIFIEdata

varnames

Optional vector with variable names

impdata.index

Selected indices of imputed datasets

svrepdesign

Object of class svyrep.design or svyimputationList

cdata

Logical inducating whether BIFIEdata object should be saved in compact format

Value

Function BIFIEdata2svrepdesign: Object of class svyrep.design or svyimputationList

Function svrepdesign2BIFIEdata: Object of class BIFIEdata

See also

See the BIFIE.data function for creating objects of class BIFIEdata in BIFIEsurvey.

See the survey::svrepdesign function in the survey package.

Examples

if (FALSE) {
#############################################################################
# EXAMPLE 1: One dataset, TIMSS replication design
#############################################################################

data(data.timss3)
data(data.timssrep)

#--- create BIFIEdata object
bdat3 <- BIFIEsurvey::BIFIE.data.jack(data.timss3, jktype="JK_TIMSS")
summary(bdat3)

#--- create survey object directly in survey package
dat3a <- as.data.frame( cbind( data.timss3, data.timssrep ) )
RR <- ncol(data.timssrep) - 1       # number of jackknife zones
svydes3a <- survey::svrepdesign(data=dat3a, weights=~TOTWGT,type="JKn",
                 repweights='w_fstr[0-9]', scale=1,  rscales=rep(1,RR), mse=TRUE )
print(svydes3a)

#--- create survey object by converting the BIFIEdata object to survey
svydes3b <- BIFIEsurvey::BIFIEdata2svrepdesign(bdat3)

#--- convert survey object into BIFIEdata object
bdat3e <- BIFIEsurvey::svrepdesign2BIFIEdata(svrepdesign=svydes3b)

#*** compare results for the mean in Mathematics scores
mod1a <- BIFIEsurvey::BIFIE.univar( bdat3, vars="ASMMAT1")
mod1b <- survey::svymean( ~ ASMMAT1, design=svydes3a )
mod1c <- survey::svymean( ~ ASMMAT1, design=svydes3b )
lavmodel <- "ASMMAT1 ~ 1"
mod1d <- BIFIEsurvey::BIFIE.lavaan.survey(lavmodel, svyrepdes=svydes3b)

#- coefficients
coef(mod1a); coef(mod1b); coef(mod1c); coef(mod1d)[1]
#- standard errors
survey::SE(mod1a); survey::SE(mod1b); survey::SE(mod1c); sqrt(vcov(mod1d)[1,1])

#############################################################################
# EXAMPLE 2: Multiply imputed datasets, TIMSS replication design
#############################################################################

data(data.timss2)
data(data.timssrep)

#--- create BIFIEdata object
bdat4 <- BIFIEsurvey::BIFIE.data( data=data.timss2, wgt="TOTWGT",
              wgtrep=data.timssrep[,-1], fayfac=1)
print(bdat4)

#--- create object with imputed datasets in survey
datL <- mitools::imputationList( data.timss2 )
RR <- ncol(data.timssrep) - 1
weights <- data.timss2[[1]]$TOTWGT
repweights <-  data.timssrep[,-1]
svydes4a <- survey::svrepdesign(data=datL, weights=weights, type="other",
               repweights=repweights, scale=1,  rscales=rep(1,RR), mse=TRUE)
print(svydes4a)

#--- create BIFIEdata object with conversion function
svydes4b <- BIFIEsurvey::BIFIEdata2svrepdesign(bdat4)

#--- reconvert survey object into BIFIEdata object
bdat4c <- BIFIEsurvey::svrepdesign2BIFIEdata(svrepdesign=svydes4b)

#*** compare results for a mean
mod1a <- BIFIEsurvey::BIFIE.univar(bdat4, vars="ASMMAT")
mod1b <- mitools::MIcombine( with(svydes4a, survey::svymean( ~ ASMMAT, design=svydes4a )))
mod1c <- mitools::MIcombine( with(svydes4b, survey::svymean( ~ ASMMAT, design=svydes4b )))

# results
coef(mod1a); coef(mod1b); coef(mod1c)
survey::SE(mod1a); survey::SE(mod1b); survey::SE(mod1c)
}