# 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`. ```r 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 ## Returns 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 ```r ## Not run: ############################################################################# # 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) ## End(Not run) ```

BIFIEdata2svrepdesign function