if (FALSE) {
#############################################################################
# EXAMPLE 1: Path model data.bifie01
#############################################################################
data(data.bifie01)
dat <- data.bifie01
# create dataset with replicate weights and plausible values
bifieobj <- BIFIEsurvey::BIFIE.data.jack( data=dat,  jktype="JK_TIMSS",
                jkzone="JKCZONE", jkrep="JKCREP", wgt="TOTWGT",
                pv_vars=c("ASMMAT","ASSSCI") )
#**************************************************************
#*** Model 1: Path model
lavmodel1 <- "
     ASMMAT ~ ASBG07A + ASBG07B  + ASBM03 + ASBM02A + ASBM02E
     # define latent variable with 2nd and 3rd item in reversed scoring
     ASBM03=~ 1*ASBM03A + (-1)*ASBM03B + (-1)*ASBM03C + 1*ASBM03D
     ASBG07A ~ ASBM02E
     ASBG07A ~~ .2*ASBG07A    # measurement error variance of .20
     ASBM02E ~~ .45*ASBM02E     # measurement error variance of .45
     ASBM02E ~ ASBM02A + ASBM02B
        "
#--- Model 1a: model calculated by gender
mod1a <- BIFIEsurvey::BIFIE.pathmodel( bifieobj, lavmodel1, group="female" )
summary(mod1a)
#--- Model 1b: Input of some known reliabilities
reliability <- c( "ASBM02B"=.6, "ASBM02A"=.8 )
mod1b <- BIFIEsurvey::BIFIE.pathmodel( bifieobj, lavmodel1, reliability=reliability)
summary(mod1b)
#**************************************************************
#*** Model 2: Linear regression with errors in predictors
# specify lavaan model
lavmodel2 <- "
     ASMMAT ~ ASBG07A + ASBG07B + ASBM03A
     ASBG07A ~~ .2*ASBG07A
        "
mod2 <- BIFIEsurvey::BIFIE.pathmodel( bifieobj, lavmodel2  )
summary(mod2)
}
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