tern (version 0.9.8)

count_patients_events_in_cols: Count patient events in columns

Description

The summarize function summarize_patients_events_in_cols() creates a layout element to summarize patient event counts in columns.

This function analyzes the elements (events) supplied via the filters_list parameter and returns a row with counts of number of patients for each event as well as the total numbers of patients and events. The id variable is used to indicate unique subject identifiers (defaults to USUBJID).

If there are multiple occurrences of the same event recorded for a patient, the event is only counted once.

Usage

summarize_patients_events_in_cols(
  lyt,
  id = "USUBJID",
  filters_list = list(),
  empty_stats = character(),
  na_str = default_na_str(),
  ...,
  .stats = c("unique", "all", names(filters_list)),
  .labels = c(unique = "Patients (All)", all = "Events (All)",
    labels_or_names(filters_list)),
  col_split = TRUE
)
s_count_patients_and_multiple_events(
  df,
  id,
  filters_list,
  empty_stats = character(),
  labelstr = "",
  custom_label = NULL
)

Value

• summarize_patients_events_in_cols() returns a layout object suitable for passing to further layouting functions, or to rtables::build_table(). Adding this function to an rtable layout will add formatted content rows containing the statistics from s_count_patients_and_multiple_events() to the table layout.

• s_count_patients_and_multiple_events() returns a list with the statistics:

  • unique: number of unique patients in df.

  • all: number of rows in df.

  • one element with the same name as in filters_list: number of rows in df, i.e. events, fulfilling the filter condition.

Arguments

lyt

(PreDataTableLayouts)
layout that analyses will be added to.

id

(string)
subject variable name.

filters_list

(named list of character)
list where each element in this list describes one type of event describe by filters, in the same format as s_count_patients_with_event(). If it has a label, then this will be used for the column title.

empty_stats

(character)
optional names of the statistics that should be returned empty such that corresponding table cells will stay blank.

na_str

(string)
string used to replace all NA or empty values in the output.

...

additional arguments for the lower level functions.

.stats

(character)
statistics to select for the table.

In addition to any statistics added using filters_list, statistic options are: 'unique', 'all'

.labels

(named character)
labels for the statistics (without indent).

col_split

(flag)
whether the columns should be split. Set to FALSE when the required column split has been done already earlier in the layout pipe.

df

(data.frame)
data set containing all analysis variables.

labelstr

(string)
label of the level of the parent split currently being summarized (must be present as second argument in Content Row Functions). See rtables::summarize_row_groups() for more information.

custom_label

(string or NULL)
if provided and labelstr is empty then this will be used as label.

Functions

• summarize_patients_events_in_cols(): Layout-creating function which can take statistics function arguments and additional format arguments. This function is a wrapper for rtables::summarize_row_groups().

• s_count_patients_and_multiple_events(): Statistics function which counts numbers of patients and multiple events defined by filters. Used as analysis function afun in summarize_patients_events_in_cols().

Examples

df <- data.frame(
  USUBJID = rep(c("id1", "id2", "id3", "id4"), c(2, 3, 1, 1)),
  ARM = c("A", "A", "B", "B", "B", "B", "A"),
  AESER = rep("Y", 7),
  AESDTH = c("Y", "Y", "N", "Y", "Y", "N", "N"),
  AEREL = c("Y", "Y", "N", "Y", "Y", "N", "Y"),
  AEDECOD = c("A", "A", "A", "B", "B", "C", "D"),
  AEBODSYS = rep(c("SOC1", "SOC2", "SOC3"), c(3, 3, 1))
)

# `summarize_patients_events_in_cols()`
basic_table() %>%
  summarize_patients_events_in_cols(
    filters_list = list(
      related = formatters::with_label(c(AEREL = "Y"), "Events (Related)"),
      fatal = c(AESDTH = "Y"),
      fatal_related = c(AEREL = "Y", AESDTH = "Y")
    ),
    custom_label = "%s Total number of patients and events"
  ) %>%
  build_table(df)