BIFIEsurvey (version 1.5-0)

BIFIE.crosstab: Cross Tabulation

Description

Creates cross tabulations and computes some effect sizes.

Usage

BIFIE.crosstab( BIFIEobj , vars1 , vars2 , vars_values1 = NULL , vars_values2 = NULL , 
     group=NULL , group_values=NULL , se=TRUE )

## S3 method for class 'BIFIE.crosstab':
summary(object,digits=3,...)

## S3 method for class 'BIFIE.crosstab':
coef(object,...)

## S3 method for class 'BIFIE.crosstab':
vcov(object,...)

Arguments

BIFIEobj

Object of class BIFIEdata

vars1

Row variable

vars2

Column variable

vars_values1

Optional vector of values of variable vars1

vars_values2

Optional vector of values of variable vars2

group

Optional grouping variable(s)

group_values

Optional vector of grouping values. This can be omitted and grouping values will be determined automatically.

se

Optional logical indicating whether statistical inference based on replication should be employed.

object

Object of class BIFIE.univar

digits

Number of digits for rounding output

...

Further arguments to be passed

Value

• A list with following entries
• stat.probs
  Statistics for joint and conditional probabilities
• stat.marg
  Statistics for marginal probabilities
• stat.es
  Statistics for effect sizes $w$ (based on $\chi^2$), Cramers $V$, Goodman's gamma, the PRE lambda measure and Kruskals tau.
• chisq.test
  Table with chi square statistics (ignoring weights and sampling scheme)
• output
  Extensive output with all replicated statistics
• ...
  More values

See Also

survey::svytable, Hmisc::wtd.table

Examples

#############################################################################
# EXAMPLE 1: Imputed TIMSS dataset
#############################################################################

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

# create BIFIE.dat object
bifieobj <- BIFIE.data( data.list=data.timss1 , wgt=  data.timss1[[1]]$TOTWGT ,
           wgtrep=data.timssrep[, -1 ] )

#--- Model 1: cross tabulation           
res1 <- BIFIE.crosstab( bifieobj , vars1="migrant" , vars2 = "books" , group="female" )
summary(res1)