Computes contingency table for one independent (column) variable and one or more dependent (row) variables.

crosstab(
  data,
  col_var,
  ...,
  add_total = FALSE,
  percentages = FALSE,
  chi_square = FALSE
)

Arguments

data

a tibble or a tdcmm model

col_var

Independent (column) variable.

...

Dependent (row) variables.

add_total

Logical indicating whether a 'Total' column should be computed. Defaults to FALSE.

percentages

Logical indicating whether to output column-wise percentages instead of absolute values. Defaults to FALSE.

chi_square

Logical indicating whether a Chi-square test should be computed. Test results will be reported via message(). Defaults to FALSE.

Value

a tdcmm model

See also

Other categorical: tab_frequencies()

Examples

WoJ %>% crosstab(reach, employment)
#> # A tibble: 3 × 5
#>   employment Local Regional National Transnational
#> * <chr>      <dbl>    <dbl>    <dbl>         <dbl>
#> 1 Freelancer    23       36      104             9
#> 2 Full-time    111      287      438            66
#> 3 Part-time     15       32       75             4
WoJ %>% crosstab(reach, employment, add_total = TRUE, percentages = TRUE, chi_square = TRUE)
#> # A tibble: 3 × 6
#>   employment Local Regional National Transnational Total
#> * <chr>      <dbl>    <dbl>    <dbl>         <dbl> <dbl>
#> 1 Freelancer 0.154   0.101     0.169        0.114  0.143
#> 2 Full-time  0.745   0.808     0.710        0.835  0.752
#> 3 Part-time  0.101   0.0901    0.122        0.0506 0.105
#> # Chi-square = 16.005, df = 6, p = 0.014, V = 0.082