Frequency Statistics
BIFIE.freq.RdComputes absolute and relative frequencies.
Arguments
- BIFIEobj
Object of class
BIFIEdata- vars
Vector of variables for which statistics should be computed
- 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.freq- digits
Number of digits for rounding output
- ...
Further arguments to be passed
Value
A list with following entries
- stat
Data frame with frequency statistics
- 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
bdat <- BIFIEsurvey::BIFIE.data( data.list=data.timss1, wgt=data.timss1[[1]]$TOTWGT,
wgtrep=data.timssrep[, -1 ] )
#> +++ Generate BIFIE.data object
#> |*****|
#> |-----|
# Frequencies for three variables
res1 <- BIFIEsurvey::BIFIE.freq( bdat, vars=c("lang", "books", "migrant" ) )
#> |*****|
#> |-----|
summary(res1)
#> ------------------------------------------------------------
#> BIFIEsurvey 3.8.0 ()
#>
#> Function 'BIFIE.freq'
#>
#> Call:
#> BIFIEsurvey::BIFIE.freq(BIFIEobj = bdat, vars = c("lang", "books",
#> "migrant"))
#>
#> Date of Analysis: 2026-01-11 08:35:25.971501
#> Time difference of 0.3153992 secs
#> Computation time: 0.3153992
#>
#> Multiply imputed dataset
#>
#> Number of persons = 4668
#> Number of imputed datasets = 5
#> Number of Jackknife zones per dataset = 75
#> Fay factor = 1
#>
#> Relative Frequencies
#> var varval Ncases Nweight perc perc_SE perc_fmi perc_df perc_VarMI
#> 1 lang 1 3472.2 60121.843 0.768 0.011 0.007 Inf 0
#> 2 lang 2 1036.4 15564.696 0.199 0.010 0.008 Inf 0
#> 3 lang 3 159.4 2646.451 0.034 0.003 0.004 Inf 0
#> 4 books 1 484.0 7889.467 0.101 0.008 0.005 Inf 0
#> 5 books 2 1213.2 20602.693 0.263 0.012 0.009 Inf 0
#> 6 books 3 1657.6 28233.896 0.360 0.010 0.004 Inf 0
#> 7 books 4 708.8 11754.811 0.150 0.008 0.032 Inf 0
#> 8 books 5 604.4 9852.122 0.126 0.008 0.017 Inf 0
#> 9 migrant 0 3614.6 62800.351 0.802 0.013 0.004 Inf 0
#> 10 migrant 1 1053.4 15532.639 0.198 0.013 0.004 Inf 0
#> perc_VarRep
#> 1 0
#> 2 0
#> 3 0
#> 4 0
#> 5 0
#> 6 0
#> 7 0
#> 8 0
#> 9 0
#> 10 0
# Frequencies splitted by gender
res2 <- BIFIEsurvey::BIFIE.freq( bdat, vars=c("lang", "books", "migrant" ),
group="female", group_values=0:1 )
#> |*****|
#> |-----|
summary(res2)
#> ------------------------------------------------------------
#> BIFIEsurvey 3.8.0 ()
#>
#> Function 'BIFIE.freq'
#>
#> Call:
#> BIFIEsurvey::BIFIE.freq(BIFIEobj = bdat, vars = c("lang", "books",
#> "migrant"), group = "female", group_values = 0:1)
#>
#> Date of Analysis: 2026-01-11 08:35:26.291337
#> Time difference of 0.06330109 secs
#> Computation time: 0.06330109
#>
#> Multiply imputed dataset
#>
#> Number of persons = 4668
#> Number of imputed datasets = 5
#> Number of Jackknife zones per dataset = 75
#> Fay factor = 1
#>
#> Relative Frequencies
#> var varval groupvar groupval Ncases Nweight perc perc_SE perc_fmi
#> 1 lang 1 female 0 1797.0 31154.878 0.776 0.013 0.008
#> 2 lang 2 female 0 491.6 7335.872 0.183 0.012 0.010
#> 3 lang 3 female 0 100.0 1639.017 0.041 0.005 0.002
#> 4 lang 1 female 1 1675.2 28966.965 0.758 0.013 0.012
#> 5 lang 2 female 1 544.8 8228.824 0.215 0.013 0.014
#> 6 lang 3 female 1 59.4 1007.434 0.026 0.003 0.009
#> 7 books 1 female 0 314.0 5258.437 0.131 0.011 0.007
#> 8 books 2 female 0 612.2 10649.303 0.265 0.013 0.020
#> 9 books 3 female 0 799.6 13544.086 0.338 0.013 0.010
#> 10 books 4 female 0 325.4 5292.094 0.132 0.008 0.018
#> 11 books 5 female 0 337.4 5385.847 0.134 0.011 0.010
#> 12 books 1 female 1 170.0 2631.030 0.069 0.008 0.002
#> 13 books 2 female 1 601.0 9953.390 0.261 0.015 0.011
#> 14 books 3 female 1 858.0 14689.810 0.385 0.013 0.009
#> 15 books 4 female 1 383.4 6462.717 0.169 0.011 0.027
#> 16 books 5 female 1 267.0 4466.275 0.117 0.009 0.039
#> 17 migrant 0 female 0 1857.6 32318.004 0.805 0.014 0.006
#> 18 migrant 1 female 0 531.0 7811.763 0.195 0.014 0.006
#> 19 migrant 0 female 1 1757.0 30482.347 0.798 0.014 0.015
#> 20 migrant 1 female 1 522.4 7720.876 0.202 0.014 0.015
#> perc_df perc_VarMI perc_VarRep
#> 1 Inf 0 0
#> 2 Inf 0 0
#> 3 Inf 0 0
#> 4 Inf 0 0
#> 5 Inf 0 0
#> 6 Inf 0 0
#> 7 Inf 0 0
#> 8 Inf 0 0
#> 9 Inf 0 0
#> 10 Inf 0 0
#> 11 Inf 0 0
#> 12 Inf 0 0
#> 13 Inf 0 0
#> 14 Inf 0 0
#> 15 Inf 0 0
#> 16 Inf 0 0
#> 17 Inf 0 0
#> 18 Inf 0 0
#> 19 Inf 0 0
#> 20 Inf 0 0
# Frequencies splitted by gender and likesc
res3 <- BIFIEsurvey::BIFIE.freq( bdat, vars=c("lang", "books", "migrant" ),
group=c("likesc","female") )
#> |*****|
#> |-----|
summary(res3)
#> ------------------------------------------------------------
#> BIFIEsurvey 3.8.0 ()
#>
#> Function 'BIFIE.freq'
#>
#> Call:
#> BIFIEsurvey::BIFIE.freq(BIFIEobj = bdat, vars = c("lang", "books",
#> "migrant"), group = c("likesc", "female"))
#>
#> Date of Analysis: 2026-01-11 08:35:26.359272
#> Time difference of 0.0707655 secs
#> Computation time: 0.0707655
#>
#> Multiply imputed dataset
#>
#> Number of persons = 4668
#> Number of imputed datasets = 5
#> Number of Jackknife zones per dataset = 75
#> Fay factor = 1
#>
#> Relative Frequencies
#> var varval groupvar1 groupval1 groupvar2 groupval2 Ncases Nweight
#> 1 lang 1 likesc 1 female 0 476.8 7753.657
#> 2 lang 2 likesc 1 female 0 184.4 2629.250
#> 3 lang 3 likesc 1 female 0 35.0 578.736
#> 4 lang 1 likesc 2 female 0 636.2 10861.713
#> 5 lang 2 likesc 2 female 0 160.4 2433.276
#> 6 lang 3 likesc 2 female 0 30.0 437.579
#> 7 lang 1 likesc 3 female 0 340.2 5988.767
#> 8 lang 2 likesc 3 female 0 66.2 1084.629
#> 9 lang 3 likesc 3 female 0 12.4 227.984
#> 10 lang 1 likesc 4 female 0 343.8 6550.741
#> 11 lang 2 likesc 4 female 0 80.6 1188.717
#> 12 lang 3 likesc 4 female 0 22.6 394.717
#> 13 lang 1 likesc 1 female 1 664.8 11056.357
#> 14 lang 2 likesc 1 female 1 291.4 4274.646
#> 15 lang 3 likesc 1 female 1 27.0 486.130
#> 16 lang 1 likesc 2 female 1 704.0 12411.598
#> 17 lang 2 likesc 2 female 1 188.8 2985.935
#> 18 lang 3 likesc 2 female 1 22.4 368.309
#> 19 lang 1 likesc 3 female 1 219.8 3973.145
#> 20 lang 2 likesc 3 female 1 44.0 650.916
#> 21 lang 3 likesc 3 female 1 7.0 107.634
#> 22 lang 1 likesc 4 female 1 86.6 1525.865
#> 23 lang 2 likesc 4 female 1 20.6 317.328
#> 24 lang 3 likesc 4 female 1 3.0 45.360
#> 25 books 1 likesc 1 female 0 93.4 1351.248
#> 26 books 2 likesc 1 female 0 182.6 3088.496
#> 27 books 3 likesc 1 female 0 219.6 3414.338
#> 28 books 4 likesc 1 female 0 94.2 1402.450
#> 29 books 5 likesc 1 female 0 106.4 1705.110
#> 30 books 1 likesc 2 female 0 89.0 1514.176
#> 31 books 2 likesc 2 female 0 210.8 3586.583
#> 32 books 3 likesc 2 female 0 291.8 4969.593
#> 33 books 4 likesc 2 female 0 119.8 1865.415
#> 34 books 5 likesc 2 female 0 115.2 1796.799
#> 35 books 1 likesc 3 female 0 53.2 873.236
#> 36 books 2 likesc 3 female 0 99.8 1882.140
#> 37 books 3 likesc 3 female 0 155.4 2655.844
#> 38 books 4 likesc 3 female 0 60.8 1078.228
#> 39 books 5 likesc 3 female 0 49.6 811.932
#> 40 books 1 likesc 4 female 0 78.4 1519.777
#> 41 books 2 likesc 4 female 0 119.0 2092.083
#> 42 books 3 likesc 4 female 0 132.8 2504.310
#> 43 books 4 likesc 4 female 0 50.6 946.000
#> 44 books 5 likesc 4 female 0 66.2 1072.006
#> 45 books 1 likesc 1 female 1 88.4 1265.480
#> 46 books 2 likesc 1 female 1 256.0 4023.914
#> 47 books 3 likesc 1 female 1 355.6 5733.673
#> 48 books 4 likesc 1 female 1 159.2 2650.750
#> 49 books 5 likesc 1 female 1 124.0 2143.315
#> 50 books 1 likesc 2 female 1 47.6 671.864
#> 51 books 2 likesc 2 female 1 247.6 4277.250
#> 52 books 3 likesc 2 female 1 367.2 6489.977
#> 53 books 4 likesc 2 female 1 158.0 2805.028
#> 54 books 5 likesc 2 female 1 94.8 1521.723
#> 55 books 1 likesc 3 female 1 17.0 389.928
#> 56 books 2 likesc 3 female 1 67.4 1178.250
#> 57 books 3 likesc 3 female 1 100.0 1744.478
#> 58 books 4 likesc 3 female 1 47.6 745.944
#> 59 books 5 likesc 3 female 1 38.8 673.095
#> 60 books 1 likesc 4 female 1 17.0 303.758
#> 61 books 2 likesc 4 female 1 30.0 473.977
#> 62 books 3 likesc 4 female 1 35.2 721.682
#> 63 books 4 likesc 4 female 1 18.6 260.995
#> 64 books 5 likesc 4 female 1 9.4 128.141
#> 65 migrant 0 likesc 1 female 0 484.6 8064.777
#> 66 migrant 1 likesc 1 female 0 211.6 2896.866
#> 67 migrant 0 likesc 2 female 0 653.4 11162.898
#> 68 migrant 1 likesc 2 female 0 173.2 2569.669
#> 69 migrant 0 likesc 3 female 0 356.4 6313.157
#> 70 migrant 1 likesc 3 female 0 62.4 988.223
#> 71 migrant 0 likesc 4 female 0 363.2 6777.172
#> 72 migrant 1 likesc 4 female 0 83.8 1357.005
#> 73 migrant 0 likesc 1 female 1 688.0 11482.736
#> 74 migrant 1 likesc 1 female 1 295.2 4334.397
#> 75 migrant 0 likesc 2 female 1 744.0 13166.386
#> 76 migrant 1 likesc 2 female 1 171.2 2599.456
#> 77 migrant 0 likesc 3 female 1 229.4 4184.403
#> 78 migrant 1 likesc 3 female 1 41.4 547.292
#> 79 migrant 0 likesc 4 female 1 95.6 1648.823
#> 80 migrant 1 likesc 4 female 1 14.6 239.730
#> perc perc_SE perc_fmi perc_df perc_VarMI perc_VarRep
#> 1 0.707 0.019 0.018 Inf 0 0.000
#> 2 0.240 0.018 0.023 Inf 0 0.000
#> 3 0.053 0.011 0.038 Inf 0 0.000
#> 4 0.791 0.016 0.005 Inf 0 0.000
#> 5 0.177 0.015 0.018 Inf 0 0.000
#> 6 0.032 0.006 0.019 Inf 0 0.000
#> 7 0.820 0.027 0.029 Inf 0 0.001
#> 8 0.149 0.027 0.019 Inf 0 0.001
#> 9 0.031 0.011 0.013 Inf 0 0.000
#> 10 0.805 0.024 0.052 Inf 0 0.001
#> 11 0.146 0.020 0.067 890.03 0 0.000
#> 12 0.049 0.012 0.006 Inf 0 0.000
#> 13 0.699 0.021 0.035 Inf 0 0.000
#> 14 0.270 0.020 0.039 Inf 0 0.000
#> 15 0.031 0.006 0.000 Inf 0 0.000
#> 16 0.787 0.017 0.029 Inf 0 0.000
#> 17 0.189 0.016 0.034 Inf 0 0.000
#> 18 0.023 0.006 0.020 Inf 0 0.000
#> 19 0.840 0.021 0.014 Inf 0 0.000
#> 20 0.138 0.018 0.020 Inf 0 0.000
#> 21 0.023 0.009 0.000 Inf 0 0.000
#> 22 0.808 0.044 0.021 Inf 0 0.002
#> 23 0.168 0.042 0.025 Inf 0 0.002
#> 24 0.024 0.015 0.001 Inf 0 0.000
#> 25 0.123 0.015 0.074 740.15 0 0.000
#> 26 0.282 0.027 0.019 Inf 0 0.001
#> 27 0.311 0.018 0.019 Inf 0 0.000
#> 28 0.128 0.017 0.014 Inf 0 0.000
#> 29 0.156 0.018 0.086 540.97 0 0.000
#> 30 0.110 0.017 0.008 Inf 0 0.000
#> 31 0.261 0.016 0.030 Inf 0 0.000
#> 32 0.362 0.021 0.056 Inf 0 0.000
#> 33 0.136 0.012 0.027 Inf 0 0.000
#> 34 0.131 0.014 0.019 Inf 0 0.000
#> 35 0.120 0.020 0.043 Inf 0 0.000
#> 36 0.258 0.030 0.099 408.77 0 0.001
#> 37 0.364 0.032 0.111 324.61 0 0.001
#> 38 0.148 0.019 0.029 Inf 0 0.000
#> 39 0.111 0.019 0.051 Inf 0 0.000
#> 40 0.187 0.024 0.049 Inf 0 0.001
#> 41 0.257 0.027 0.022 Inf 0 0.001
#> 42 0.308 0.029 0.045 Inf 0 0.001
#> 43 0.116 0.016 0.015 Inf 0 0.000
#> 44 0.132 0.019 0.041 Inf 0 0.000
#> 45 0.080 0.008 0.016 Inf 0 0.000
#> 46 0.254 0.021 0.030 Inf 0 0.000
#> 47 0.363 0.020 0.030 Inf 0 0.000
#> 48 0.168 0.014 0.036 Inf 0 0.000
#> 49 0.136 0.015 0.047 Inf 0 0.000
#> 50 0.043 0.008 0.028 Inf 0 0.000
#> 51 0.271 0.020 0.015 Inf 0 0.000
#> 52 0.412 0.019 0.011 Inf 0 0.000
#> 53 0.178 0.018 0.011 Inf 0 0.000
#> 54 0.097 0.013 0.026 Inf 0 0.000
#> 55 0.082 0.035 0.004 Inf 0 0.001
#> 56 0.249 0.031 0.036 Inf 0 0.001
#> 57 0.369 0.035 0.010 Inf 0 0.001
#> 58 0.158 0.024 0.032 Inf 0 0.001
#> 59 0.142 0.026 0.019 Inf 0 0.001
#> 60 0.161 0.037 0.006 Inf 0 0.001
#> 61 0.251 0.048 0.020 Inf 0 0.002
#> 62 0.382 0.052 0.070 825.93 0 0.003
#> 63 0.138 0.034 0.037 Inf 0 0.001
#> 64 0.068 0.022 0.212 89.41 0 0.000
#> 65 0.736 0.020 0.006 Inf 0 0.000
#> 66 0.264 0.020 0.006 Inf 0 0.000
#> 67 0.813 0.018 0.016 Inf 0 0.000
#> 68 0.187 0.018 0.016 Inf 0 0.000
#> 69 0.865 0.035 0.013 Inf 0 0.001
#> 70 0.135 0.035 0.013 Inf 0 0.001
#> 71 0.833 0.020 0.037 Inf 0 0.000
#> 72 0.167 0.020 0.037 Inf 0 0.000
#> 73 0.726 0.020 0.021 Inf 0 0.000
#> 74 0.274 0.020 0.021 Inf 0 0.000
#> 75 0.835 0.019 0.049 Inf 0 0.000
#> 76 0.165 0.019 0.049 Inf 0 0.000
#> 77 0.884 0.022 0.031 Inf 0 0.000
#> 78 0.116 0.022 0.031 Inf 0 0.000
#> 79 0.873 0.039 0.043 Inf 0 0.001
#> 80 0.127 0.039 0.043 Inf 0 0.001