Add a missing subject row into a count summary.

This function calculates the number of subjects missing from a particular group of results. The calculation is done by examining the total number of subjects potentially available from the Header N values within the result column, and finding the difference with the total number of subjects present in the result group. Note that for accurate results, the subject variable needs to be defined using the `set_distinct_by()` function. As with other methods, this function instructs how distinct results should be identified.

Usage

add_missing_subjects_row(e, fmt = NULL, sort_value = NULL)

Arguments

e

A `count_layer` object

fmt

An f_str object used to format the total row. If none is provided, display is based on the layer formatting.

sort_value

The value that will appear in the ordering column for total rows. This must be a numeric value.

Examples

tplyr_table(mtcars, gear) %>%
  add_layer(
    group_count(cyl) %>%
      add_missing_subjects_row(f_str("xxxx", n))
   ) %>%
   build()
#> Warning: 	Population data was not set separately from the target data.
#> 	Missing subject counts may be misleading in this scenario.
#> 	Did you mean to use `set_missing_count() instead?
#> # A tibble: 4 × 6
#>   row_label1 var1_3        var1_4        var1_5      ord_layer_index ord_layer_1
#>   <chr>      <chr>         <chr>         <chr>                 <int>       <dbl>
#> 1 4          " 1 (  6.7%)" " 8 ( 66.7%)" " 2 ( 40.0…               1           1
#> 2 6          " 2 ( 13.3%)" " 4 ( 33.3%)" " 1 ( 20.0…               1           2
#> 3 8          "12 ( 80.0%)" " 0 (  0.0%)" " 2 ( 40.0…               1           3
#> 4 Missing    "    "        "    "        "    "                    1           4