refactor geom sd and fix custom stat order

NEWS.md

@@ -2,14 +2,17 @@
 
 ### Enhancements
 * Refactored `count_abnormal()`, `count_abnormal_by_baseline()`, `count_abnormal_by_marked()`, `count_abnormal_by_worst_grade()`, and `count_abnormal_lab_worsen_by_baseline()` to work without `make_afun()`.
+* Added `geom_sd` and `geom_mean_sd` to `s_summary()` default available statistics.
 
 ### Bug Fixes
 * Fixed bug in `a_count_patients_with_flags()` preventing select custom label and indentation specification formats from being applied.
 * Fixed bug in `tabulate_rsp_subgroups` and `tabulate_survival_subgroups` preventing the `pct` option from having an effect when adding a risk difference column.
+* Fixed bug with the order of `.stats` when adding custom statistical functions.
 
 ### Miscellaneous
 * Removed internal function `ungroup_stats()` and replaced its usage with the `get_*_from_stats()` functions.
 * Began deprecation of the unused `table_names` argument to `count_abnormal_lab_worsen_by_baseline()`.
+* Added warnings for `geom_mean` statistical output.
 
 # tern 0.9.7
 

R/analyze_variables.R

@@ -234,10 +234,25 @@ s_summary.numeric <- function(x, control = control_analyze_vars(), ...) {
 
   y$cv <- c("cv" = unname(y$sd) / unname(y$mean) * 100)
 
-  # Convert negative values to NA for log calculation.
+  # Geometric Mean - Convert negative values to NA for log calculation.
+  geom_verbose <- args_list[["geom_verbose"]] %||% FALSE # Additional info if requested
+  checkmate::assert_flag(geom_verbose)
   x_no_negative_vals <- x
+  if (identical(x_no_negative_vals, numeric())) {
+    x_no_negative_vals <- NA
+  }
   x_no_negative_vals[x_no_negative_vals <= 0] <- NA
+  if (geom_verbose) {
+    if (any(x <= 0)) {
+      warning("Negative values were converted to NA for calculation of the geometric mean.")
+    }
+    if (all(is.na(x_no_negative_vals))) {
+      warning("Since all values are negative or NA, the geometric mean is NA.")
+    }
+  }
   y$geom_mean <- c("geom_mean" = exp(mean(log(x_no_negative_vals), na.rm = FALSE)))
+  y$geom_sd <- c("geom_sd" = geom_sd <- exp(sd(log(x_no_negative_vals), na.rm = FALSE)))
+  y$geom_mean_sd <- c(y$geom_mean, y$geom_sd)
   geom_mean_ci <- stat_mean_ci(x, conf_level = control$conf_level, na.rm = FALSE, gg_helper = FALSE, geom_mean = TRUE)
   y$geom_mean_ci <- formatters::with_label(geom_mean_ci, paste("Geometric Mean", f_conf_level(control$conf_level)))
 
@@ -549,7 +564,7 @@ a_summary <- function(x,
 
   # Check if there are user-defined functions
   default_and_custom_stats_list <- .split_std_from_custom_stats(.stats)
-  .stats <- default_and_custom_stats_list$default_stats
+  .stats <- default_and_custom_stats_list$all_stats # just the labels of stats
   custom_stat_functions <- default_and_custom_stats_list$custom_stats
 
   # Correction of the pval indication if it is numeric or counts
@@ -588,12 +603,11 @@ a_summary <- function(x,
 
   # Fill in with stats defaults if needed
   met_grp <- paste0(c("analyze_vars", type), collapse = "_")
-  .stats <- c(
-    get_stats(met_grp,
-      stats_in = .stats,
-      add_pval = dots_extra_args$compare_with_ref_group %||% FALSE
-    ),
-    names(custom_stat_functions) # Additional stats from custom functions
+  .stats <- get_stats(
+    met_grp,
+    stats_in = .stats,
+    custom_stats_in = names(custom_stat_functions),
+    add_pval = dots_extra_args$compare_with_ref_group %||% FALSE
   )
 
   x_stats <- x_stats[.stats]

R/count_values.R

@@ -118,7 +118,7 @@ a_count_values <- function(x,
 
   # Check for user-defined functions
   default_and_custom_stats_list <- .split_std_from_custom_stats(.stats)
-  .stats <- default_and_custom_stats_list$default_stats
+  .stats <- default_and_custom_stats_list$all_stats # just the labels of stats
   custom_stat_functions <- default_and_custom_stats_list$custom_stats
 
   # Add extra parameters to the s_* function
@@ -139,9 +139,10 @@ a_count_values <- function(x,
   )
 
   # Fill in formatting defaults
-  .stats <- c(
-    get_stats("analyze_vars_counts", stats_in = .stats),
-    names(custom_stat_functions) # Additional stats from custom functions
+  .stats <- get_stats(
+    "analyze_vars_counts",
+    stats_in = .stats,
+    custom_stats_in = names(custom_stat_functions),
   )
   .formats <- get_formats_from_stats(.stats, .formats)
   .labels <- get_labels_from_stats(.stats, .labels)

R/summarize_change.R

@@ -67,7 +67,7 @@ a_change_from_baseline <- function(df,
 
   # Check if there are user-defined functions
   default_and_custom_stats_list <- .split_std_from_custom_stats(.stats)
-  .stats <- default_and_custom_stats_list$default_stats
+  .stats <- default_and_custom_stats_list$all_stats # just the labels of stats
   custom_stat_functions <- default_and_custom_stats_list$custom_stats
 
   # Adding automatically extra parameters to the statistic function (see ?rtables::additional_fun_params)
@@ -88,9 +88,10 @@ a_change_from_baseline <- function(df,
   )
 
   # Fill in with formatting defaults if needed
-  .stats <- c(
-    get_stats("analyze_vars_numeric", stats_in = .stats),
-    names(custom_stat_functions) # Additional stats from custom functions
+  .stats <- get_stats(
+    "analyze_vars_numeric",
+    stats_in = .stats,
+    custom_stats_in = names(custom_stat_functions),
   )
   .formats <- get_formats_from_stats(.stats, .formats)
   .labels <- get_labels_from_stats(.stats, .labels)

R/utils_default_stats_formats_labels.R

@@ -33,7 +33,9 @@ NULL
 #' @param method_groups (`character`)\cr indicates the statistical method group (`tern` analyze function)
 #'   to retrieve default statistics for. A character vector can be used to specify more than one statistical
 #'   method group.
-#' @param stats_in (`character`)\cr statistics to retrieve for the selected method group.
+#' @param stats_in (`character`)\cr statistics to retrieve for the selected method group. If custom statistical
+#'   functions are used, `stats_in` needs to have them in too.
+#' @param custom_stats_in (`character`)\cr custom statistics to add to the default statistics.
 #' @param add_pval (`flag`)\cr should `"pval"` (or `"pval_counts"` if `method_groups` contains
 #'   `"analyze_vars_counts"`) be added to the statistical methods?
 #'
@@ -57,9 +59,11 @@ NULL
 #' get_stats(c("count_occurrences", "analyze_vars_counts"))
 #'
 #' @export
-get_stats <- function(method_groups = "analyze_vars_numeric", stats_in = NULL, add_pval = FALSE) {
+get_stats <- function(method_groups = "analyze_vars_numeric",
+                      stats_in = NULL, custom_stats_in = NULL, add_pval = FALSE) {
   checkmate::assert_character(method_groups)
   checkmate::assert_character(stats_in, null.ok = TRUE)
+  checkmate::assert_character(custom_stats_in, null.ok = TRUE)
   checkmate::assert_flag(add_pval)
 
   # Default is still numeric
@@ -82,6 +86,9 @@ get_stats <- function(method_groups = "analyze_vars_numeric", stats_in = NULL, a
     out <- unique(c(out, out_tmp))
   }
 
+  # Add custom stats
+  out <- c(out, custom_stats_in)
+
   # If you added pval to the stats_in you certainly want it
   if (!is.null(stats_in) && any(grepl("^pval", stats_in))) {
     stats_in_pval_value <- stats_in[grepl("^pval", stats_in)]
@@ -157,7 +164,7 @@ get_stat_names <- function(stat_results, stat_names_in = NULL) {
     if (is.null(nm)) {
       nm <- rep(NA_character_, length(si)) # no statistical names
     }
-    return(nm)
+    nm
   })
 
   # Modify some with custom stat names
@@ -172,16 +179,18 @@ get_stat_names <- function(stat_results, stat_names_in = NULL) {
 
 # Utility function used to separate custom stats (user-defined functions) from defaults
 .split_std_from_custom_stats <- function(stats_in) {
-  out <- list(default_stats = NULL, custom_stats = NULL)
+  out <- list(default_stats = NULL, custom_stats = NULL, all_stats = NULL)
   if (is.list(stats_in)) {
     is_custom_fnc <- sapply(stats_in, is.function)
     checkmate::assert_list(stats_in[is_custom_fnc], types = "function", names = "named")
     out[["custom_stats"]] <- stats_in[is_custom_fnc]
     out[["default_stats"]] <- unlist(stats_in[!is_custom_fnc])
+    all_stats <- names(stats_in) # to keep the order
+    all_stats[!is_custom_fnc] <- out[["default_stats"]]
+    out[["all_stats"]] <- all_stats
   } else {
-    out[["default_stats"]] <- stats_in
+    out[["default_stats"]] <- out[["all_stats"]] <- stats_in
   }
-
   out
 }
 
@@ -500,7 +509,7 @@ tern_default_stats <- list(
   analyze_vars_numeric = c(
     "n", "sum", "mean", "sd", "se", "mean_sd", "mean_se", "mean_ci", "mean_sei", "mean_sdi", "mean_pval",
     "median", "mad", "median_ci", "quantiles", "iqr", "range", "min", "max", "median_range", "cv",
-    "geom_mean", "geom_mean_ci", "geom_cv",
+    "geom_mean", "geom_sd", "geom_mean_sd", "geom_mean_ci", "geom_cv",
     "median_ci_3d",
     "mean_ci_3d", "geom_mean_ci_3d"
   ),
@@ -580,6 +589,8 @@ tern_default_formats <- c(
   median_range = "xx.x (xx.x - xx.x)",
   cv = "xx.x",
   geom_mean = "xx.x",
+  geom_sd = "xx.x",
+  geom_mean_sd = "xx.x (xx.x)",
   geom_mean_ci = "(xx.xx, xx.xx)",
   geom_mean_ci_3d = "xx.xx (xx.xx - xx.xx)",
   geom_cv = "xx.x",
@@ -631,6 +642,8 @@ tern_default_labels <- c(
   median_range = "Median (Min - Max)",
   cv = "CV (%)",
   geom_mean = "Geometric Mean",
+  geom_sd = "Geometric SD",
+  geom_mean_sd = "Geometric Mean (SD)",
   geom_mean_ci = "Geometric Mean 95% CI",
   geom_mean_ci_3d = "Geometric Mean (95% CI)",
   geom_cv = "CV % Geometric Mean",

tests/testthat/_snaps/analyze_variables.md

@@ -117,7 +117,15 @@
 
       $geom_mean
       geom_mean 
-            NaN 
+             NA 
+
+      $geom_sd
+      geom_sd 
+           NA 
+
+      $geom_mean_sd
+      geom_mean   geom_sd 
+             NA        NA 
 
       $geom_mean_ci
       mean_ci_lwr mean_ci_upr 
@@ -131,7 +139,7 @@
 
       $geom_mean_ci_3d
         geom_mean mean_ci_lwr mean_ci_upr 
-              NaN          NA          NA 
+               NA          NA          NA 
       attr(,"label")
       [1] "Geometric Mean (95% CI)"
 
@@ -257,6 +265,14 @@
       geom_mean 
               1 
 
+      $geom_sd
+      geom_sd 
+           NA 
+
+      $geom_mean_sd
+      geom_mean   geom_sd 
+              1        NA 
+
       $geom_mean_ci
       mean_ci_lwr mean_ci_upr 
                NA          NA 
@@ -395,6 +411,14 @@
       geom_mean 
              NA 
 
+      $geom_sd
+      geom_sd 
+           NA 
+
+      $geom_mean_sd
+      geom_mean   geom_sd 
+             NA        NA 
+
       $geom_mean_ci
       mean_ci_lwr mean_ci_upr 
                NA          NA 
@@ -533,6 +557,14 @@
       geom_mean 
        1.414214 
 
+      $geom_sd
+       geom_sd 
+      1.632527 
+
+      $geom_mean_sd
+      geom_mean   geom_sd 
+       1.414214  1.632527 
+
       $geom_mean_ci
        mean_ci_lwr  mean_ci_upr 
         0.01729978 115.60839614 
@@ -671,6 +703,14 @@
       geom_mean 
        4.842534 
 
+      $geom_sd
+       geom_sd 
+      2.252326 
+
+      $geom_mean_sd
+      geom_mean   geom_sd 
+       4.842534  2.252326 
+
       $geom_mean_ci
       mean_ci_lwr mean_ci_upr 
          2.456211    9.547283 
@@ -1388,11 +1428,13 @@
       20    median_range    0.3 (-0.8 - 1.6)          0          Median (Min - Max)
       21              cv               590.4          0                      CV (%)
       22       geom_mean                  NA          0              Geometric Mean
-      23    geom_mean_ci                  NA          0       Geometric Mean 95% CI
-      24         geom_cv                  NA          0         CV % Geometric Mean
-      25    median_ci_3d 0.26 (-0.82 - 0.74)          0             Median (95% CI)
-      26      mean_ci_3d 0.13 (-0.43 - 0.69)          0               Mean (95% CI)
-      27 geom_mean_ci_3d                  NA          0     Geometric Mean (95% CI)
+      23         geom_sd                  NA          0                Geometric SD
+      24    geom_mean_sd                  NA          0         Geometric Mean (SD)
+      25    geom_mean_ci                  NA          0       Geometric Mean 95% CI
+      26         geom_cv                  NA          0         CV % Geometric Mean
+      27    median_ci_3d 0.26 (-0.82 - 0.74)          0             Median (95% CI)
+      28      mean_ci_3d 0.13 (-0.43 - 0.69)          0               Mean (95% CI)
+      29 geom_mean_ci_3d                  NA          0     Geometric Mean (95% CI)
 
 ---
 
@@ -1523,12 +1565,14 @@
       20    median_range    5.0 (3.0 - 5.9)          0          Median (Min - Max)
       21              cv               19.6          0                      CV (%)
       22       geom_mean                4.8          0              Geometric Mean
-      23    geom_mean_ci       (4.07, 5.58)          0       Geometric Mean 95% CI
-      24         geom_cv               22.3          0         CV % Geometric Mean
-      25    median_ci_3d 5.01 (3.53 - 5.78)          0             Median (95% CI)
-      26      mean_ci_3d 4.87 (4.18 - 5.55)          0               Mean (95% CI)
-      27 geom_mean_ci_3d 4.77 (4.07 - 5.58)          0     Geometric Mean (95% CI)
-      28            pval            <0.0001          0            p-value (t-test)
+      23         geom_sd                1.2          0                Geometric SD
+      24    geom_mean_sd          4.8 (1.2)          0         Geometric Mean (SD)
+      25    geom_mean_ci       (4.07, 5.58)          0       Geometric Mean 95% CI
+      26         geom_cv               22.3          0         CV % Geometric Mean
+      27    median_ci_3d 5.01 (3.53 - 5.78)          0             Median (95% CI)
+      28      mean_ci_3d 4.87 (4.18 - 5.55)          0               Mean (95% CI)
+      29 geom_mean_ci_3d 4.77 (4.07 - 5.58)          0     Geometric Mean (95% CI)
+      30            pval            <0.0001          0            p-value (t-test)
 
 ---
 

tests/testthat/_snaps/compare_variables.md

@@ -9,7 +9,8 @@
       [13] "median"          "mad"             "median_ci"       "median_ci_3d"   
       [17] "quantiles"       "iqr"             "range"           "min"            
       [21] "max"             "median_range"    "cv"              "geom_mean"      
-      [25] "geom_mean_ci"    "geom_cv"         "geom_mean_ci_3d" "pval"           
+      [25] "geom_sd"         "geom_mean_sd"    "geom_mean_ci"    "geom_cv"        
+      [29] "geom_mean_ci_3d" "pval"           
 
 # s_compare for numeric does not give p-value when not at least 2 values in each group