Skip to contents

Pivots a summarised_result object based on the column names in header, generating specific column names for subsequent header formatting in gtTable and fxTable functions.

Usage

formatHeader(
  result,
  header,
  delim = "\n",
  includeHeaderName = TRUE,
  includeHeaderKey = TRUE
)

Arguments

result

A summarised_result.

header

Names of the columns to make headers. Names that doesn't correspond to a column of the table result, will be used as headers at the defined position.

delim

Delimiter to use to separate headers.

includeHeaderName

Whether to include the column name as header.

includeHeaderKey

Whether to include the header key (header, header_name, header_level) before each header type in the column names.

Value

A tibble with rows pivotted into columns with key names for subsequent header formatting.

Examples

result <- mockSummarisedResult()

result |>
  formatHeader(
    header = c(
      "Study cohorts", "group_level", "Study strata", "strata_name",
      "strata_level"
    ),
    includeHeaderName = FALSE
  )
#> # A tibble: 7 × 27
#>   result_id cdm_name group_name  variable_name   variable_level estimate_name
#>       <int> <chr>    <chr>       <chr>           <chr>          <chr>        
#> 1         1 mock     cohort_name number subjects NA             count        
#> 2         1 mock     cohort_name age             NA             mean         
#> 3         1 mock     cohort_name age             NA             sd           
#> 4         1 mock     cohort_name Medications     Amoxiciline    count        
#> 5         1 mock     cohort_name Medications     Amoxiciline    percentage   
#> 6         1 mock     cohort_name Medications     Ibuprofen      count        
#> 7         1 mock     cohort_name Medications     Ibuprofen      percentage   
#> # ℹ 21 more variables: estimate_type <chr>, additional_name <chr>,
#> #   additional_level <chr>,
#> #   `[header]Study cohorts\n[header_level]cohort1\n[header]Study strata\n[header_level]overall\n[header_level]overall` <chr>,
#> #   `[header]Study cohorts\n[header_level]cohort1\n[header]Study strata\n[header_level]age_group &&& sex\n[header_level]<40 &&& Male` <chr>,
#> #   `[header]Study cohorts\n[header_level]cohort1\n[header]Study strata\n[header_level]age_group &&& sex\n[header_level]>=40 &&& Male` <chr>,
#> #   `[header]Study cohorts\n[header_level]cohort1\n[header]Study strata\n[header_level]age_group &&& sex\n[header_level]<40 &&& Female` <chr>,
#> #   `[header]Study cohorts\n[header_level]cohort1\n[header]Study strata\n[header_level]age_group &&& sex\n[header_level]>=40 &&& Female` <chr>, …