BIFIEsurvey (version 1.5-0)

BIFIE.data.jack: Create BIFIE.data Object with Jackknife Zones

Description

Creates a BIFIE.data objects for designs with jackknife zones, especially for TIMSS/PIRLS and PISA studies.

Usage

BIFIE.data.jack(data, wgt = NULL, jktype = "JK_TIMSS", pv_vars = NULL, 
     jkzone = NULL, jkrep = NULL, jkfac = NULL, fayfac = NULL , 
     wgtrep = "W_FSTR" , pvpre = paste0("PV",1:5) , ngr=100 ,
     seed = .Random.seed , cdata=FALSE)

Arguments

data

Data frame: Can be a single or a list of multiply-imputed datasets

wgt

A string indicating the label of case weight. If jktype="JK_TIMSS", then wgt="TOTWGT".

pv_vars

An optional vector of plausible values which define multiply-imputed datasets.

jktype

Type of jackknife procedure for creating the BIFIE.data object. jktype="JK_TIMSS" refers to TIMSS/PIRLS datasets. The type "JK_GROUP" creates jackknife weights based on a user defined grouping, the type "JK_

jkzone

Jackknife zones. If jktype="JK_TIMSS", then jkzone="JKZONE".

jkrep

Jackknife replicate factors. If jktype="JK_TIMSS", then jkrep="JKREP".

jkfac

Factor for multiplying jackknife replicate weights. If jktype="JK_TIMSS", then jkfac=2.

fayfac

Fay factor for statistical inference. The default is set to NULL.

wgtrep

Variables in the dataset which refer to the replicate weights. In case of cdata=TRUE, the replicate weights are deleted from datalistM.

pvpre

Only applicable for jktype="RW_PISA". The vector contains the prefixes of the variables containing plausible values.

ngr

Number of randomly created groups in "JK_RANDOM".

seed

The simulation seed if "JK_RANDOM" is chosen. If seed=NULL, then the grouping is done according the order in the dataset.

cdata

An optional logical indicating whether the BIFIEdata object should be compactly saved. The default is FALSE.

Value

• Object of class BIFIEdata

See Also

BIFIE.data, BIFIE.data.boot

Examples

#############################################################################
# EXAMPLE 1: Convert TIMSS dataset to BIFIE.data object
#############################################################################

data(data.timss3)

# define plausible values
pv_vars <- c("ASMMAT" , "ASSSCI" )
# create BIFIE.data objects -> 5 imputed datasets
bdat1 <- BIFIE.data.jack( data=data.timss3  ,  pv_vars = pv_vars ,
             jktype="JK_TIMSS"  )
summary(bdat1)

# create BIFIE.data objects -> all PVs are included in one dataset
bdat2 <- BIFIE.data.jack( data=data.timss3  ,  jktype="JK_TIMSS"  )
summary(bdat2)

#############################################################################
# EXAMPLE 2: Creation of Jackknife zones and replicate weights for data.test1
#############################################################################

data(data.test1)

# create jackknife zones based on random group creation
bdat1 <- BIFIE.data.jack( data = data.test1 ,  jktype="JK_RANDOM" , ngr = 50  )
summary(bdat1)
stat1 <- BIFIE.univar( bdat1 , vars ="math" ,  group="stratum" )
summary(stat1)

# random creation of groups and inclusion of weights
bdat2 <- BIFIE.data.jack( data = data.test1 ,  jktype="JK_RANDOM" , ngr = 75 , seed=987 ,
                wgt="wgtstud")
summary(bdat2)
stat2 <- BIFIE.univar( bdat2 , vars ="math" ,  group="stratum" )
summary(stat2)

# using idclass as jackknife zones
bdat3 <- BIFIE.data.jack( data = data.test1 ,  jktype="JK_GROUP" , jkzone="idclass" , 
                wgt="wgtstud")
summary(bdat3)
stat3 <- BIFIE.univar( bdat3 , vars ="math" ,  group="stratum" )
summary(stat3)

# create BIFIEdata object with a list of imputed datasets
dataList <- list( data.test1 , data.test1 , data.test1 )
bdat4 <- BIFIE.data.jack( data = dataList ,  jktype="JK_GROUP" , jkzone="idclass" , 
                wgt="wgtstud")
summary(bdat4)                

#############################################################################
# EXAMPLE 3: Converting a PISA dataset into a BIFIEdata object
#############################################################################

data(data.pisaNLD)

# BIFIEdata with cdata=FALSE
bifieobj <- BIFIE.data.jack( data.pisaNLD , jktype = "RW_PISA" , cdata=FALSE )
summary(bifieobj)
# BIFIEdata with cdata=TRUE
bifieobj1 <- BIFIE.data.jack( data.pisaNLD , jktype = "RW_PISA" , cdata=TRUE )
summary(bifieobj1)