new unified get_ref_info

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: junco
 Title: Create Common Tables and Listings Used in Clinical Trials
-Version: 0.1.6.9000
+Version: 0.1.6.9001
 Date: 2026-05-22
 Authors@R: c(
     person("Gabriel", "Becker", , "gabembecker@gmail.com", role = c("cre", "aut"),

NAMESPACE

@@ -66,7 +66,6 @@ export(get_visit_levels)
 export(grouped_cols_w_diffs)
 export(h_extract_coxreg_multivar)
 export(h_get_design_mat)
-export(h_get_trtvar_refpath)
 export(h_tidy_pool)
 export(in_column)
 export(inches_to_spaces)

NEWS.md

@@ -1,4 +1,4 @@
-# junco 0.1.6.9000
+# junco 0.1.6.9001
 
 ### Fixed
 - Fixed `get_ref_info()` to accept ref_path = NULL (#359).
@@ -9,11 +9,14 @@
 
 ### Changed
 
+- Updated several analysis functions to use `h_get_cur_trt_grp()` (#295).
+- Replaced `h_get_trtvar_refpath()` with `h_get_cur_trt_grp()` (#295).
+- Updated `get_ref_info()` for matching column split paths (#295).
 - Added the new helper function `factor_by_order()` (#425).
 - Renamed `in_ref_col()` to `in_column()` and renamed its `ref_path` argument
   to `col_path`.
 - Updated `in_ref_col()` to accept `ref_path = NULL` (#404).
-- Added the new helper functions `cur_col_split_path()` and `in_ref_col()` to
+- Added the new helper functions `cur_col_split_path()` and `in_column()` to
   support custom analysis functions that depend on the current column split
   context (#404).
 - Added a default value for the `label` argument in `c_summary_subset_label()`.
@@ -42,6 +45,7 @@
 - Add extra statistics to `a_eair100_j` and introduce scaling factor `num_p_year` (default = 100) (#361)
 
 ### Added
+- Added `strict_match()` for uniquely matching a value in the odd or even positions of a character vector.
 - Added `categorize_pval()` for assigning p-values to validated, user-defined categories.
 - Added `pool_rubin_scalar()` and `pool_z_stat()` for pooling scalar estimates and z statistics across imputations.
 - Added `resp_multiple_imputation()` to impute missing binary responses across scenarios and pool CMH risk-difference and p-value results.

R/a_freq_j.R

@@ -801,6 +801,9 @@ a_freq_j <- function(
   colgroup = NULL,
   countsource = c("df", "altdf", "altdf_subset")
 ) {
+  checkmate::check_character(ref_path, min.len = 2L)
+  checkmate::assert_true(length(ref_path) %% 2L == 0L)
+
   denom <- match.arg(denom)
   method <- match.arg(method)
 
@@ -913,7 +916,6 @@ a_freq_j <- function(
     if (riskdiff && is.null(ref_path)) {
       stop("argument ref_path cannot be NULL.")
     }
-    ### denom N_colgroup should not be used in layout with risk diff columns
     if (denom == "N_colgroup") {
       stop(
         "denom N_colgroup cannot be used in a layout with risk diff columns."
@@ -923,28 +925,11 @@ a_freq_j <- function(
       trt_var <- NULL
       ctrl_grp <- NULL
       cur_trt_grp <- NULL
-    }
-
-    if (riskdiff) {
-      trt_var_refpath <- h_get_trtvar_refpath(
-        ref_path,
-        .spl_context,
-        df
-      )
-      # trt_var_refpath is list with elements
-      # trt_var trt_var_refspec cur_trt_grp ctrl_grp
-      # make these elements available in current environment
-      trt_var <- trt_var_refpath$trt_var
-      trt_var_refspec <- trt_var_refpath$trt_var_refspec
-      cur_trt_grp <- trt_var_refpath$cur_trt_grp
-      ctrl_grp <- trt_var_refpath$ctrl_grp
-      # for combined facet, denom_df value for the treatment group needs update
-      new_denomdf <- upd_denom_df_combo(
-        new_denomdf,
-        trt_var,
-        cur_trt_grp,
-        .spl_context
-      )
+    } else {
+      trt_var <- ref_path[length(ref_path) - 1L]
+      ctrl_grp <- ref_path[length(ref_path)]
+      stopifnot(ctrl_grp %in% levels(df[[trt_var]]))
+      cur_trt_grp <- h_get_cur_trt_grp(trt_var, .spl_context)
 
       if (!is.null(colgroup) && trt_var == colgroup) {
         stop(
@@ -953,6 +938,13 @@ a_freq_j <- function(
              Either remove risk difference columns from layout, set riskdiff = FALSE, or update colgroup."
         )
       }
+
+      new_denomdf <- upd_denom_df_combo(
+        new_denomdf,
+        trt_var,
+        cur_trt_grp,
+        .spl_context
+      )
     }
 
     x_stats <- s_rel_risk_val_j(

R/a_freq_resp_var_j.R

@@ -46,34 +46,38 @@
 #'
 #' result
 a_freq_resp_var_j <- function(
-    df,
-    .var,
-    .df_row,
-    .N_col,
-    .spl_context,
-    resp_var = NULL,
-    id = "USUBJID",
-    drop_levels = FALSE,
-    riskdiff = TRUE,
-    ref_path = NULL,
-    variables = formals(s_proportion_diff)$variables,
-    conf_level = formals(s_proportion_diff)$conf_level,
-    method = c(
-      "wald",
-      "waldcc",
-      "cmh",
-      "ha",
-      "newcombe",
-      "newcombecc",
-      "strat_newcombe",
-      "strat_newcombecc",
-      "cmh_sato",
-      "cmh_mn",
-      "uncond_exact_diff"
-    ),
-    weights_method = formals(s_proportion_diff)$weights_method,
-    .formats = NULL,
-    na_str = rep("NA", 3)) {
+  df,
+  .var,
+  .df_row,
+  .N_col,
+  .spl_context,
+  resp_var = NULL,
+  id = "USUBJID",
+  drop_levels = FALSE,
+  riskdiff = TRUE,
+  ref_path = NULL,
+  variables = formals(s_proportion_diff)$variables,
+  conf_level = formals(s_proportion_diff)$conf_level,
+  method = c(
+    "wald",
+    "waldcc",
+    "cmh",
+    "ha",
+    "newcombe",
+    "newcombecc",
+    "strat_newcombe",
+    "strat_newcombecc",
+    "cmh_sato",
+    "cmh_mn",
+    "uncond_exact_diff"
+  ),
+  weights_method = formals(s_proportion_diff)$weights_method,
+  .formats = NULL,
+  na_str = rep("NA", 3)
+) {
+  checkmate::check_character(ref_path, min.len = 2L)
+  checkmate::assert_true(length(ref_path) %% 2L == 0L)
+
   # ---- Derive statistics: xx / xx (xx.x%)
 
   if (is.null(resp_var)) {
@@ -137,18 +141,9 @@ a_freq_resp_var_j <- function(
   inriskdiffcol <- grepl("difference", tolower(colid), fixed = TRUE)
 
   if (riskdiff) {
-    trt_var_refpath <- h_get_trtvar_refpath(
-      ref_path,
-      .spl_context,
-      df
-    )
-    # trt_var_refpath is list with elements
-    # trt_var trt_var_refspec cur_trt_grp ctrl_grp
-    # make these elements available in current environment
-    trt_var <- trt_var_refpath$trt_var
-    trt_var_refspec <- trt_var_refpath$trt_var_refspec
-    cur_trt_grp <- trt_var_refpath$cur_trt_grp
-    ctrl_grp <- trt_var_refpath$ctrl_grp
+    trt_var <- ref_path[length(ref_path) - 1L]
+    ctrl_grp <- ref_path[length(ref_path)]
+    cur_trt_grp <- h_get_cur_trt_grp(trt_var, .spl_context)
   }
 
   fn <- function(levii) {

R/a_summarize_aval_chg_diff.R

@@ -66,23 +66,24 @@ s_aval_chg_col1 <- function(df, .var, denom, .N_col, id, indatavar) {
 }
 
 s_aval_chg_col23_diff <- function(
-    df,
-    .var,
-    .df_row,
-    .ref_group,
-    .in_ref_col,
-    ancova,
-    interaction_y,
-    interaction_item,
-    conf_level,
-    variables,
-    trt_var,
-    ctrl_grp,
-    cur_param,
-    cur_lvl,
-    weights_emmeans,
-    method_combo,
-    weights_combo) {
+  df,
+  .var,
+  .df_row,
+  .ref_group,
+  .in_ref_col,
+  ancova,
+  interaction_y,
+  interaction_item,
+  conf_level,
+  variables,
+  trt_var,
+  ctrl_grp,
+  cur_param,
+  cur_lvl,
+  weights_emmeans,
+  method_combo,
+  weights_combo
+) {
   .df_row <- subset(.df_row, !is.na(.df_row[[.var]]))
   df <- subset(df, !is.na(df[[.var]]))
   .ref_group <- subset(.ref_group, !is.na(.ref_group[[.var]]))
@@ -374,29 +375,33 @@ format_xxd <- function(str, d = 0, .df_row, formatting_fun = NULL) {
 #' result
 #' @family Inclusion of ANCOVA Functions
 a_summarize_aval_chg_diff_j <- function(
-    df,
-    .df_row,
-    .spl_context,
-    ancova = FALSE,
-    comp_btw_group = TRUE,
-    ref_path = NULL,
-    .N_col,
-    denom = c("N", ".N_col"),
-    indatavar = NULL,
-    d = 0,
-    id = "USUBJID",
-    interaction_y = FALSE,
-    interaction_item = NULL,
-    conf_level = 0.95,
-    variables = list(arm = "TRT01A", covariates = NULL),
-    format_na_str = "",
-    .stats = list(col1 = "count_denom_frac", col23 = "mean_ci_3d", coldiff = "meandiff_ci_3d"),
-    .formats = list(col1 = NULL, col23 = "xx.dx (xx.dx, xx.dx)", coldiff = "xx.dx (xx.dx, xx.dx)"),
-    .formats_fun = list(col1 = jjcsformat_count_denom_fraction, col23 = jjcsformat_xx, coldiff = jjcsformat_xx),
-    multivars = c("AVAL", "AVAL", "CHG"),
-    weights_emmeans = NULL,
-    method_combo = c("contrasts", "collapse"),
-    weights_combo = NULL) {
+  df,
+  .df_row,
+  .spl_context,
+  ancova = FALSE,
+  comp_btw_group = TRUE,
+  ref_path = NULL,
+  .N_col,
+  denom = c("N", ".N_col"),
+  indatavar = NULL,
+  d = 0,
+  id = "USUBJID",
+  interaction_y = FALSE,
+  interaction_item = NULL,
+  conf_level = 0.95,
+  variables = list(arm = "TRT01A", covariates = NULL),
+  format_na_str = "",
+  .stats = list(col1 = "count_denom_frac", col23 = "mean_ci_3d", coldiff = "meandiff_ci_3d"),
+  .formats = list(col1 = NULL, col23 = "xx.dx (xx.dx, xx.dx)", coldiff = "xx.dx (xx.dx, xx.dx)"),
+  .formats_fun = list(col1 = jjcsformat_count_denom_fraction, col23 = jjcsformat_xx, coldiff = jjcsformat_xx),
+  multivars = c("AVAL", "AVAL", "CHG"),
+  weights_emmeans = NULL,
+  method_combo = c("contrasts", "collapse"),
+  weights_combo = NULL
+) {
+  checkmate::check_character(ref_path, min.len = 2L)
+  checkmate::assert_true(length(ref_path) %% 2L == 0L)
+
   denom <- match.arg(denom)
   method_combo <- match.arg(method_combo)
 
@@ -474,22 +479,11 @@ a_summarize_aval_chg_diff_j <- function(
 
   .in_ref_col <- FALSE
   .ref_group <- NULL
+  ctrl_grp <- NULL
   if (comp_btw_group) {
-    trt_var_refspec <- utils::tail(ref_path, n = 2)[1]
-    checkmate::assert_true(identical(trt_var, trt_var_refspec))
-    # ctrl_grp
-    ctrl_grp <- utils::tail(ref_path, n = 1)
-
-    ### check that ctrl_grp is a level of the treatment variable, in case riskdiff is requested
-    if (!ctrl_grp %in% levels(df[[trt_var]])) {
-      stop(paste0(
-        "control group specification in ref_path argument (",
-        ctrl_grp,
-        ") is not a level of your treatment group variable (",
-        trt_var,
-        ")."
-      ))
-    }
+    checkmate::assert_true(identical(trt_var, ref_path[length(ref_path) - 1L]))
+    ctrl_grp <- ref_path[length(ref_path)]
+    stopifnot(ctrl_grp %in% levels(df[[trt_var]]))
 
     if (trt_val == ctrl_grp) .in_ref_col <- TRUE