Cross Tabulation
BIFIE.crosstab.RdCreates cross tabulations and computes some effect sizes.
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.
- output
Extensive output with all replicated statistics
- ...
More values
Examples
#############################################################################
# EXAMPLE 1: Imputed TIMSS dataset
#############################################################################
data(data.timss1)
data(data.timssrep)
# create BIFIE.dat object
bifieobj <- BIFIEsurvey::BIFIE.data( data.list=data.timss1, wgt=data.timss1[[1]]$TOTWGT,
wgtrep=data.timssrep[, -1 ] )
#> +++ Generate BIFIE.data object
#> |*****|
#> |-----|
#--- Model 1: cross tabulation
res1 <- BIFIEsurvey::BIFIE.crosstab( bifieobj, vars1="migrant",
vars2="books", group="female" )
#> |*****|
#> |-----|
summary(res1)
#> ------------------------------------------------------------
#> BIFIEsurvey 3.8.0 ()
#>
#> Function 'BIFIE.crosstab'
#>
#> Call:
#> BIFIEsurvey::BIFIE.crosstab(BIFIEobj = bifieobj, vars1 = "migrant",
#> vars2 = "books", group = "female")
#>
#> Date of Analysis: 2026-01-11 08:35:20.187442
#> Time difference of 0.03271055 secs
#> Computation time: 0.03271055
#>
#> Multiply imputed dataset
#>
#> Number of persons = 4668
#> Number of imputed datasets = 5
#> Number of Jackknife zones per dataset = 75
#> Fay factor = 1
#>
#> Joint and Conditional Probabilities
#> prob var1 varval1 var2 varval2 group groupval Ncases Nweight est
#> 1 joint migrant 0 books 1 female 0 162.6 2929.601 0.073
#> 2 joint migrant 0 books 2 female 0 434.2 7965.610 0.198
#> 3 joint migrant 0 books 3 female 0 663.4 11627.561 0.290
#> 4 joint migrant 0 books 4 female 0 293.6 4876.792 0.122
#> 5 joint migrant 0 books 5 female 0 303.8 4918.441 0.123
#> 6 joint migrant 1 books 1 female 0 151.4 2328.836 0.058
#> 7 joint migrant 1 books 2 female 0 178.0 2683.693 0.067
#> 8 joint migrant 1 books 3 female 0 136.2 1916.525 0.048
#> 9 joint migrant 1 books 4 female 0 31.8 415.302 0.010
#> 10 joint migrant 1 books 5 female 0 33.6 467.407 0.012
#> 11 joint migrant 0 books 1 female 1 71.2 1270.661 0.033
#> 12 joint migrant 0 books 2 female 1 385.0 6870.760 0.180
#> 13 joint migrant 0 books 3 female 1 715.0 12483.328 0.327
#> 14 joint migrant 0 books 4 female 1 355.2 6051.650 0.158
#> 15 joint migrant 0 books 5 female 1 230.6 3805.948 0.100
#> 16 joint migrant 1 books 1 female 1 98.8 1360.369 0.036
#> 17 joint migrant 1 books 2 female 1 216.0 3082.630 0.081
#> 18 joint migrant 1 books 3 female 1 143.0 2206.482 0.058
#> 19 joint migrant 1 books 4 female 1 28.2 411.067 0.011
#> 20 joint migrant 1 books 5 female 1 36.4 660.327 0.017
#> 21 rowcond migrant 0 books 1 female 0 162.6 2929.601 0.091
#> 22 rowcond migrant 0 books 2 female 0 434.2 7965.610 0.246
#> 23 rowcond migrant 0 books 3 female 0 663.4 11627.561 0.360
#> 24 rowcond migrant 0 books 4 female 0 293.6 4876.792 0.151
#> 25 rowcond migrant 0 books 5 female 0 303.8 4918.441 0.152
#> 26 rowcond migrant 1 books 1 female 0 151.4 2328.836 0.298
#> 27 rowcond migrant 1 books 2 female 0 178.0 2683.693 0.344
#> 28 rowcond migrant 1 books 3 female 0 136.2 1916.525 0.245
#> 29 rowcond migrant 1 books 4 female 0 31.8 415.302 0.053
#> 30 rowcond migrant 1 books 5 female 0 33.6 467.407 0.060
#> 31 rowcond migrant 0 books 1 female 1 71.2 1270.661 0.042
#> 32 rowcond migrant 0 books 2 female 1 385.0 6870.760 0.225
#> 33 rowcond migrant 0 books 3 female 1 715.0 12483.328 0.410
#> 34 rowcond migrant 0 books 4 female 1 355.2 6051.650 0.199
#> 35 rowcond migrant 0 books 5 female 1 230.6 3805.948 0.125
#> 36 rowcond migrant 1 books 1 female 1 98.8 1360.369 0.176
#> 37 rowcond migrant 1 books 2 female 1 216.0 3082.630 0.399
#> 38 rowcond migrant 1 books 3 female 1 143.0 2206.482 0.286
#> 39 rowcond migrant 1 books 4 female 1 28.2 411.067 0.053
#> 40 rowcond migrant 1 books 5 female 1 36.4 660.327 0.086
#> 41 colcond migrant 0 books 1 female 0 162.6 2929.601 0.557
#> 42 colcond migrant 0 books 2 female 0 434.2 7965.610 0.748
#> 43 colcond migrant 0 books 3 female 0 663.4 11627.561 0.858
#> 44 colcond migrant 0 books 4 female 0 293.6 4876.792 0.922
#> 45 colcond migrant 0 books 5 female 0 303.8 4918.441 0.913
#> 46 colcond migrant 1 books 1 female 0 151.4 2328.836 0.443
#> 47 colcond migrant 1 books 2 female 0 178.0 2683.693 0.252
#> 48 colcond migrant 1 books 3 female 0 136.2 1916.525 0.142
#> 49 colcond migrant 1 books 4 female 0 31.8 415.302 0.078
#> 50 colcond migrant 1 books 5 female 0 33.6 467.407 0.087
#> 51 colcond migrant 0 books 1 female 1 71.2 1270.661 0.483
#> 52 colcond migrant 0 books 2 female 1 385.0 6870.760 0.690
#> 53 colcond migrant 0 books 3 female 1 715.0 12483.328 0.850
#> 54 colcond migrant 0 books 4 female 1 355.2 6051.650 0.936
#> 55 colcond migrant 0 books 5 female 1 230.6 3805.948 0.852
#> 56 colcond migrant 1 books 1 female 1 98.8 1360.369 0.517
#> 57 colcond migrant 1 books 2 female 1 216.0 3082.630 0.310
#> 58 colcond migrant 1 books 3 female 1 143.0 2206.482 0.150
#> 59 colcond migrant 1 books 4 female 1 28.2 411.067 0.064
#> 60 colcond migrant 1 books 5 female 1 36.4 660.327 0.148
#> SE fmi df VarMI VarRep
#> 1 0.007 0.011 Inf 0 0.000
#> 2 0.011 0.033 Inf 0 0.000
#> 3 0.013 0.018 Inf 0 0.000
#> 4 0.008 0.026 Inf 0 0.000
#> 5 0.011 0.015 Inf 0 0.000
#> 6 0.007 0.034 Inf 0 0.000
#> 7 0.009 0.012 Inf 0 0.000
#> 8 0.005 0.032 Inf 0 0.000
#> 9 0.002 0.034 Inf 0 0.000
#> 10 0.002 0.101 388.46 0 0.000
#> 11 0.007 0.011 Inf 0 0.000
#> 12 0.011 0.035 Inf 0 0.000
#> 13 0.015 0.005 Inf 0 0.000
#> 14 0.011 0.019 Inf 0 0.000
#> 15 0.009 0.031 Inf 0 0.000
#> 16 0.004 0.020 Inf 0 0.000
#> 17 0.009 0.009 Inf 0 0.000
#> 18 0.007 0.026 Inf 0 0.000
#> 19 0.003 0.023 Inf 0 0.000
#> 20 0.003 0.018 Inf 0 0.000
#> 21 0.009 0.013 Inf 0 0.000
#> 22 0.013 0.032 Inf 0 0.000
#> 23 0.015 0.025 Inf 0 0.000
#> 24 0.009 0.027 Inf 0 0.000
#> 25 0.012 0.014 Inf 0 0.000
#> 26 0.024 0.102 382.83 0 0.001
#> 27 0.031 0.013 Inf 0 0.001
#> 28 0.022 0.038 Inf 0 0.000
#> 29 0.011 0.024 Inf 0 0.000
#> 30 0.013 0.076 699.03 0 0.000
#> 31 0.009 0.010 Inf 0 0.000
#> 32 0.014 0.025 Inf 0 0.000
#> 33 0.016 0.014 Inf 0 0.000
#> 34 0.013 0.028 Inf 0 0.000
#> 35 0.011 0.028 Inf 0 0.000
#> 36 0.017 0.016 Inf 0 0.000
#> 37 0.030 0.003 Inf 0 0.001
#> 38 0.026 0.038 Inf 0 0.001
#> 39 0.013 0.022 Inf 0 0.000
#> 40 0.018 0.020 Inf 0 0.000
#> 41 0.034 0.047 Inf 0 0.001
#> 42 0.028 0.018 Inf 0 0.001
#> 43 0.014 0.039 Inf 0 0.000
#> 44 0.015 0.043 Inf 0 0.000
#> 45 0.017 0.117 290.86 0 0.000
#> 46 0.034 0.047 Inf 0 0.001
#> 47 0.028 0.018 Inf 0 0.001
#> 48 0.014 0.039 Inf 0 0.000
#> 49 0.015 0.043 Inf 0 0.000
#> 50 0.017 0.117 290.86 0 0.000
#> 51 0.065 0.022 Inf 0 0.004
#> 52 0.025 0.030 Inf 0 0.001
#> 53 0.018 0.020 Inf 0 0.000
#> 54 0.015 0.013 Inf 0 0.000
#> 55 0.027 0.010 Inf 0 0.001
#> 56 0.065 0.022 Inf 0 0.004
#> 57 0.025 0.030 Inf 0 0.001
#> 58 0.018 0.020 Inf 0 0.000
#> 59 0.015 0.013 Inf 0 0.000
#> 60 0.027 0.010 Inf 0 0.001
#>
#> Marginal Probabilities
#> prob var varval group groupval est SE fmi df VarMI VarRep
#> 1 rowmarg migrant 0 female 0 0.805 0.014 0.006 Inf 0 0
#> 2 rowmarg migrant 1 female 0 0.195 0.014 0.006 Inf 0 0
#> 3 rowmarg migrant 0 female 1 0.798 0.014 0.015 Inf 0 0
#> 4 rowmarg migrant 1 female 1 0.202 0.014 0.015 Inf 0 0
#> 5 colmarg books 1 female 0 0.131 0.011 0.007 Inf 0 0
#> 6 colmarg books 2 female 0 0.265 0.013 0.020 Inf 0 0
#> 7 colmarg books 3 female 0 0.338 0.013 0.010 Inf 0 0
#> 8 colmarg books 4 female 0 0.132 0.008 0.018 Inf 0 0
#> 9 colmarg books 5 female 0 0.134 0.011 0.010 Inf 0 0
#> 10 colmarg books 1 female 1 0.069 0.008 0.002 Inf 0 0
#> 11 colmarg books 2 female 1 0.261 0.015 0.011 Inf 0 0
#> 12 colmarg books 3 female 1 0.385 0.013 0.009 Inf 0 0
#> 13 colmarg books 4 female 1 0.169 0.011 0.027 Inf 0 0
#> 14 colmarg books 5 female 1 0.117 0.009 0.039 Inf 0 0
#>
#> Effect Sizes
#> parm group groupval est SE fmi df VarMI VarRep
#> 1 w female 0 0.291 0.022 0.128 244.47 0 0.000
#> 2 w female 1 0.300 0.036 0.024 Inf 0 0.001
#> 3 V female 0 0.291 0.022 0.128 244.47 0 0.000
#> 4 V female 1 0.300 0.036 0.024 Inf 0 0.001
#> 5 gamma female 0 -0.485 0.033 0.115 301.63 0 0.001
#> 6 gamma female 1 -0.467 0.054 0.009 Inf 0 0.003
#> 7 lambda female 0 0.022 0.011 0.009 Inf 0 0.000
#> 8 lambda_X female 0 0.000 0.000 0.000 Inf 0 0.000
#> 9 lambda_Y female 0 0.029 0.014 0.009 Inf 0 0.000
#> 10 lambda female 1 0.031 0.020 0.024 Inf 0 0.000
#> 11 lambda_X female 1 0.012 0.041 0.025 Inf 0 0.002
#> 12 lambda_Y female 1 0.037 0.017 0.015 Inf 0 0.000
#> 13 tau female 0 0.037 0.006 0.095 439.20 0 0.000
#> 14 tau_X female 0 0.085 0.013 0.128 243.88 0 0.000
#> 15 tau_Y female 0 0.017 0.003 0.088 515.56 0 0.000
#> 16 tau female 1 0.040 0.010 0.027 Inf 0 0.000
#> 17 tau_X female 1 0.090 0.022 0.023 Inf 0 0.000
#> 18 tau_Y female 1 0.019 0.005 0.027 Inf 0 0.000