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| Original file line number | Diff line number | Diff line change |
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| #' Count the Number of Patients with Particular Flags | ||
| #' | ||
| #' @description `r lifecycle::badge("stable")` | ||
| #' | ||
| #' The primary analysis variable `.var` denotes the unique patient identifier. | ||
| #' | ||
| #' @inheritParams argument_convention | ||
| #' | ||
| #' @seealso [count_patients_with_event] | ||
| #' | ||
| #' @name count_patients_with_flags | ||
| NULL | ||
|
|
||
| #' @describeIn count_patients_with_flags Statistics function which counts the number of patients for which | ||
| #' a particular flag variable is `TRUE`. | ||
| #' | ||
| #' @inheritParams summarize_variables | ||
| #' @param .var (`character`)\cr name of the column that contains the unique identifier. | ||
| #' @param flag_variables (`character`)\cr a character vector specifying the names of `logical` | ||
| #' variables from analysis dataset used for counting the number of unique identifiers. | ||
| #' | ||
| #' @return | ||
| #' * `s_count_patients_with_flags()` returns the count and the fraction of unique identifiers with each particular | ||
| #' flag as a list of statistics `n`, `count`, `count_fraction`, and `n_blq`, with one element per flag. | ||
| #' | ||
| #' @examples | ||
| #' library(dplyr) | ||
| #' | ||
| #' # `s_count_patients_with_flags()` | ||
| #' | ||
| #' # Add labelled flag variables to analysis dataset. | ||
| #' adae <- tern_ex_adae %>% | ||
| #' mutate( | ||
| #' fl1 = TRUE, | ||
| #' fl2 = TRTEMFL == "Y", | ||
| #' fl3 = TRTEMFL == "Y" & AEOUT == "FATAL", | ||
| #' fl4 = TRTEMFL == "Y" & AEOUT == "FATAL" & AEREL == "Y" | ||
| #' ) | ||
| #' labels <- c( | ||
| #' "fl1" = "Total AEs", | ||
| #' "fl2" = "Total number of patients with at least one adverse event", | ||
| #' "fl3" = "Total number of patients with fatal AEs", | ||
| #' "fl4" = "Total number of patients with related fatal AEs" | ||
| #' ) | ||
| #' formatters::var_labels(adae)[names(labels)] <- labels | ||
| #' | ||
| #' s_count_patients_with_flags( | ||
| #' adae, | ||
| #' "SUBJID", | ||
| #' flag_variables = c("fl1", "fl2", "fl3", "fl4"), | ||
| #' denom = "N_col", | ||
| #' .N_col = 1000 | ||
| #' ) | ||
| #' | ||
| #' @export | ||
| s_count_patients_with_flags <- function(df, | ||
| .var, | ||
| flag_variables, | ||
| .N_col, # nolint | ||
| .N_row, # nolint | ||
| denom = c("n", "N_row", "N_col")) { | ||
| if (is.null(names(flag_variables))) flag_variables <- stats::setNames(flag_variables, flag_variables) | ||
| flag_names <- unname(flag_variables) | ||
| flag_variables <- names(flag_variables) | ||
|
|
||
| checkmate::assert_subset(flag_variables, colnames(df)) | ||
| temp <- sapply(flag_variables, function(x) { | ||
| tmp <- Map(function(y) which(df[[y]]), x) | ||
| position_satisfy_flags <- Reduce(intersect, tmp) | ||
| id_satisfy_flags <- as.character(unique(df[position_satisfy_flags, ][[.var]])) | ||
| s_count_values( | ||
| as.character(unique(df[[.var]])), | ||
| id_satisfy_flags, | ||
| denom = denom, | ||
| .N_col = .N_col, | ||
| .N_row = .N_row | ||
| ) | ||
| }) | ||
| colnames(temp) <- flag_names | ||
| temp <- data.frame(t(temp)) | ||
| result <- temp %>% as.list() | ||
| if (length(flag_variables) == 1) { | ||
| for (i in 1:3) names(result[[i]]) <- flag_names[1] | ||
| } | ||
| result | ||
| } | ||
|
|
||
| #' @describeIn count_patients_with_flags Formatted analysis function which is used as `afun` | ||
| #' in `count_patients_with_flags()`. | ||
| #' | ||
| #' @return | ||
| #' * `a_count_patients_with_flags()` returns the corresponding list with formatted [rtables::CellValue()]. | ||
| #' | ||
| #' @examples | ||
| #' # We need to ungroup `count_fraction` first so that the `rtables` formatting | ||
| #' # function `format_count_fraction()` can be applied correctly. | ||
| #' | ||
| #' # `a_count_patients_with_flags()` | ||
| #' | ||
| #' afun <- make_afun(a_count_patients_with_flags, | ||
| #' .stats = "count_fraction", | ||
| #' .ungroup_stats = "count_fraction" | ||
| #' ) | ||
| #' afun( | ||
| #' adae, | ||
| #' .N_col = 10L, | ||
| #' .N_row = 10L, | ||
| #' .var = "USUBJID", | ||
| #' flag_variables = c("fl1", "fl2", "fl3", "fl4") | ||
| #' ) | ||
| #' | ||
| #' @export | ||
| a_count_patients_with_flags <- make_afun( | ||
| s_count_patients_with_flags, | ||
| .formats = c("count_fraction" = format_count_fraction_fixed_dp) | ||
| ) | ||
|
|
||
| #' @describeIn count_patients_with_flags Layout-creating function which can take statistics function | ||
| #' arguments and additional format arguments. This function is a wrapper for [rtables::analyze()]. | ||
| #' | ||
| #' @return | ||
| #' * `count_patients_with_flags()` 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 rows containing | ||
| #' the statistics from `s_count_patients_with_flags()` to the table layout. | ||
| #' | ||
| #' @examples | ||
| #' # `count_patients_with_flags()` | ||
| #' | ||
| #' lyt2 <- basic_table() %>% | ||
| #' split_cols_by("ARM") %>% | ||
| #' add_colcounts() %>% | ||
| #' count_patients_with_flags( | ||
| #' "SUBJID", | ||
| #' flag_variables = formatters::var_labels(adae[, c("fl1", "fl2", "fl3", "fl4")]), | ||
| #' denom = "N_col" | ||
| #' ) | ||
| #' build_table(lyt2, adae, alt_counts_df = tern_ex_adsl) | ||
| #' | ||
| #' @export | ||
| count_patients_with_flags <- function(lyt, | ||
| var, | ||
| var_labels = var, | ||
| show_labels = "hidden", | ||
| ..., | ||
| table_names = paste0("tbl_flags_", var), | ||
| .stats = "count_fraction", | ||
| .formats = NULL, | ||
| .indent_mods = NULL) { | ||
| afun <- make_afun( | ||
| a_count_patients_with_flags, | ||
| .stats = .stats, | ||
| .formats = .formats, | ||
| .indent_mods = .indent_mods, | ||
| .ungroup_stats = .stats | ||
| ) | ||
|
|
||
| lyt <- analyze( | ||
| lyt = lyt, | ||
| vars = var, | ||
| var_labels = var_labels, | ||
| show_labels = show_labels, | ||
| afun = afun, | ||
| table_names = table_names, | ||
| extra_args = list(...) | ||
| ) | ||
|
|
||
| lyt | ||
| } |
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