Find the proper function to apply to each statistical and column block pairing and use the metadata associated with each column block for the function's arguments

app_methods(agg, column, week, group, data, totals, filter = NA)

Arguments

agg: the statistic to apply given the block name
column: the column to apply that statistic too, and class of the column dictated by the data frame it came from
week: the week if needed for calculation
group: whether to perform a group_by and if so by which column
data: the dataset to perform all functions on
totals: the totals data frame that contains denominator N's use when calculating column percentages
filter: a string denoting the additional filter to apply to the dataset

Value

the table corresponding to the proper function to perform given the supplied column. This is used within a map to apply to all blocks inside the table generator module.

Examples

if(interactive()){
  data(example_dat1, package = "tidyCDISC")

  # Create non-missing table section
  app_methods("NON_MISSING", 
             structure("USUBJID", class = c("character", "ADSL")), NA, 
             "TRT01P", example_dat1$AE, example_dat1$totals)
            
  # Create ANOVA table section
  app_methods("ANOVA", 
            structure("TEMP", class = c("character", "BDS")), "Week 2", 
            "TRT01P", example_dat1$BDS, example_dat1$totals)

  # Create change table section
  app_methods("CHG", 
            structure("WEIGHT", class = c("character", "BDS")), "Week 12", 
            "TRT01P", example_dat1$BDS, example_dat1$totals)

  # Create mean table section
  app_methods("MEAN", 
            structure("PULSE", class = c("character", "BDS")), "Baseline", 
            "TRT01P", example_dat1$BDS, example_dat1$totals)
}