BIFIE.data: Creates an Object of Class 'BIFIEdata'

In BIFIEsurvey: Tools for Survey Statistics in Educational Assessment

Creates an Object of Class BIFIEdata

Description

This function creates an object of class BIFIEdata. Finite sampling correction of statistical inferences can be conducted by specifying appropriate input in the fayfac argument.

Usage

BIFIE.data(data.list, wgt=NULL, wgtrep=NULL, fayfac=1, pv_vars=NULL,
     pvpre=NULL, cdata=FALSE, NMI=FALSE)

## S3 method for class 'BIFIEdata'
summary(object,...)

## S3 method for class 'BIFIEdata'
print(x,...)

Arguments

data.list	List of multiply imputed datasets. Can be also a list of list of imputed datasets in case of nested multiple imputation. Then, the argument NMI=TRUE must be specified.
wgt	A string indicating the label of case weight or a vector containing all case weights.
wgtrep	Optional vector of replicate weights
fayfac	Fay factor for calculating standard errors, a numeric value. If finite sampling correction is requested, an appropriate vector input can be used (see Example 3).
pv_vars	Optional vector for names of plausible values, see BIFIE.data.jack.
pvpre	Optional vector for prefixes of plausible values, see BIFIE.data.jack.
cdata	An optional logical indicating whether the BIFIEdata object should be compactly saved. The default is FALSE.
NMI	Optional logical indicating whether data.list is obtained by nested multiple imputation.
object	Object of class BIFIEdata
x	Object of class BIFIEdata
...	Further arguments to be passed

Value

An object of class BIFIEdata saved in a non-compact or compact way, see value cdata. The following entries are included in the list:

datalistM	Stacked list of imputed datasets (if cdata=FALSE)
wgt	Vector with case weights
wgtrep	Matrix with replicate weights
Nimp	Number of imputed datasets
N	Number of observations in a dataset
dat1	Last imputed dataset
varnames	Vector with variable names
fayfac	Fay factor.
RR	Number of replicate weights
NMI	Logical indicating whether the dataset is nested multiply imputed.
cdata	Logical indicating whether the BIFIEdata object is in compact format (cdata=TRUE) or in a non-compact format (cdata=FALSE).
Nvars	Number of variables
variables	Data frame including some informations about variables. All transformations are saved in the column source.
datalistM_ind	Data frame with response indicators (if cdata=TRUE)
datalistM_imputed	Data frame with imputed values (if cdata=TRUE)

See Also

See BIFIE.data.transform for data transformations on BIFIEdata objects.

For saving and loading BIFIEdata objects see save.BIFIEdata.

For converting PIRLS/TIMSS or PISA datasets into BIFIEdata objects see BIFIE.data.jack.

See the BIFIEdata2svrepdesign function for converting BIFIEdata objects to objects used in the survey package.

Examples

#############################################################################
# EXAMPLE 1: Create BIFIEdata object with multiply-imputed TIMSS data
#############################################################################
data(data.timss1)
data(data.timssrep)

bdat <- BIFIEsurvey::BIFIE.data( data.list=data.timss1, wgt=data.timss1[[1]]$TOTWGT,
            wgtrep=data.timssrep[, -1 ] )
summary(bdat)
# create BIFIEdata object in a compact way
bdat2 <- BIFIEsurvey::BIFIE.data( data.list=data.timss1, wgt=data.timss1[[1]]$TOTWGT,
            wgtrep=data.timssrep[, -1 ], cdata=TRUE)
summary(bdat2)

## Not run: 
#############################################################################
# EXAMPLE 2: Create BIFIEdata object with one dataset
#############################################################################
data(data.timss2)

# use first dataset with missing data from data.timss2
bdat <- BIFIEsurvey::BIFIE.data( data.list=data.timss2[[1]], wgt=data.timss2[[1]]$TOTWGT)

## End(Not run)

#############################################################################
# EXAMPLE 3: BIFIEdata objects with finite sampling correction
#############################################################################

data(data.timss1)
data(data.timssrep)

#-----
# BIFIEdata object without finite sampling correction
bdat1 <- BIFIEsurvey::BIFIE.data( data.list=data.timss1, wgt=data.timss1[[1]]$TOTWGT,
            wgtrep=data.timssrep[, -1 ] )
summary(bdat1)

#-----
# generate BIFIEdata object with finite sampling correction by adjusting
# the "fayfac" factor
bdat2 <- bdat1
#-- modify "fayfac" constant
fayfac0 <- bdat1$fayfac
# set fayfac=.75 for the first 50 replication zones (25% of students in the
# population were sampled) and fayfac=.20 for replication zones 51-75
# (meaning that 80% of students were sampled)
fayfac <- rep( fayfac0, bdat1$RR )
fayfac[1:50] <- fayfac0 * .75
fayfac[51:75] <- fayfac0 * .20
# include this modified "fayfac" factor in bdat2
bdat2$fayfac <- fayfac
summary(bdat2)
summary(bdat1)

#---- compare some univariate statistics
# no finite sampling correction
res1 <- BIFIEsurvey::BIFIE.univar( bdat1, vars="ASMMAT")
summary(res1)
# finite sampling correction
res2 <- BIFIEsurvey::BIFIE.univar( bdat2, vars="ASMMAT")
summary(res2)

## Not run: 
#############################################################################
# EXAMPLE 4: Create BIFIEdata object with nested multiply imputed dataset
#############################################################################

data(data.timss4)
data(data.timssrep)

# nested imputed dataset, save it in compact format
bdat <- BIFIEsurvey::BIFIE.data( data.list=data.timss4,
            wgt=data.timss4[[1]][[1]]$TOTWGT, wgtrep=data.timssrep[, -1 ],
            NMI=TRUE, cdata=TRUE )
summary(bdat)

## End(Not run)

BIFIEsurvey documentation built on May 29, 2024, 2:52 a.m.