Dev

NAMESPACE

@@ -6,6 +6,7 @@ S3method(plot,dunnett_test_result)
 S3method(print,RSCABS)
 S3method(print,StepDownRSCABS)
 S3method(print,drcComp)
+S3method(print,dunn_test_result)
 S3method(print,dunnett_test_result)
 S3method(print,stepDownTrendBinom)
 S3method(print,tskresult)
@@ -19,11 +20,13 @@ export(ECx_rating)
 export(ED.ZG)
 export(ED.plus)
 export(RSCABK)
+export(SpearmanKarber_modified)
 export(Tarone.test)
 export(Tarone.trend.test)
 export(addECxCI)
 export(aggregate_from_individual_simple)
 export(aggregate_from_individual_tidy)
+export(analyze_SK)
 export(backCalcSE)
 export(broom_dunnett)
 export(broom_williams)
@@ -33,12 +36,14 @@ export(calcTaronesTest)
 export(calculate_noec_rstatix)
 export(cochranArmitageTrendTest)
 export(compare_to_control_fisher)
+export(compute_mdd_williams)
 export(contEndpoint)
 export(convert2Score)
 export(convert_fish_data)
 export(create_contingency_table)
 export(dose.p.glmmPQL)
 export(drcCompare)
+export(dunn_test)
 export(dunnett_test)
 export(expand_to_individual_simple)
 export(expand_to_individual_tidy)

NEWS.md

@@ -0,0 +1,3 @@
+# drcHelper (development version)
+
+* Initial CRAN submission preparation.

R/MDD.R

@@ -0,0 +1,57 @@
+#' Calculate MDD% for a Williams Test Result
+#'
+#' @param williams_obj The tibble result from broom_williams.
+#' @param data The original dataframe used for the test.
+#' @param formula The formula used for the test, e.g., Response ~ Dose.
+#' @return A tibble with Dose, MDD, and MDD_pct.
+#' @export
+compute_mdd_williams <- function(williams_obj, data, formula) {
+
+  if (!inherits(williams_obj, "tbl_df") || !all(c("comparison", "t'-crit") %in% names(williams_obj))) {
+    stop("williams_obj must be the result from a broom_williams call.")
+  }
+  if (nrow(williams_obj) == 0) return(tibble::tibble(Dose=numeric(), MDD_pct=numeric()))
+
+  # 1. Extract variable names
+  resp_name <- all.vars(formula)[1]
+  dose_name <- all.vars(formula)[2] # Correctly gets "Dose"
+
+  # --- START OF FIX ---
+  # Create a local copy of the data to avoid modifying the original
+  local_data <- data
+
+  # Ensure the dose column is a factor with control (0) as the first level.
+  # This makes the function robust and independent of the input data's column type.
+  dose_values <- local_data[[dose_name]]
+  factor_levels <- sort(unique(dose_values))
+  local_data$dose_factor_col <- factor(dose_values, levels = factor_levels)
+
+  # Define the new, reliable factor column name and update formula for aov()
+  factor_col_name <- "dose_factor_col"
+  aov_formula <- as.formula(paste(resp_name, "~", factor_col_name))
+  # --- END OF FIX ---
+
+  # 2. Extract info from the Williams test object
+  Tcrit <- williams_obj[["t'-crit"]]
+  doses <- as.numeric(gsub(" - 0.*", "", williams_obj$comparison))
+
+  # 3. Get ANOVA stats (MSE) using the corrected formula and local data
+  aov_fit <- stats::aov(aov_formula, data = local_data)
+  mse <- summary(aov_fit)[[1]]["Residuals", "Mean Sq"]
+
+  # 4. Get control group stats using the reliable factor column
+  control_level <- levels(local_data[[factor_col_name]])[1]
+  ctrl_data <- local_data[local_data[[factor_col_name]] == control_level, ]
+  mu_c <- mean(ctrl_data[[resp_name]], na.rm = TRUE)
+  n_c <- nrow(ctrl_data)
+
+  # 5. Get treatment sample sizes
+  n_t <- sapply(doses, function(d) sum(local_data[[dose_name]] == d))
+
+  # 6. Calculate MDD and MDD%
+  SE_diff <- sqrt(mse * (1 / n_c + 1 / n_t))
+  MDD <- Tcrit * SE_diff
+  MDD_pct <- 100 * MDD / abs(mu_c)
+
+  tibble::tibble(Dose = doses, MDD_pct = MDD_pct)
+}

R/RSCABS.R

@@ -7,19 +7,19 @@
 
 #' Run RSCABS test (DEPRECATED)
 #'
-#' @description 
-#' **DEPRECATED**: Please use [step_down_RSCABS()] instead for new code.
-#' 
+#' @description
+#' **DEPRECATED**: Please use [drcHelper::step_down_RSCABS()] instead for new code.
+#'
 #' Runs the Rao-Scott adjusted Cochran-Armitage trend test by slices (RSCABS)
 #' analysis.The function is adapted from the archived version of RSCABS developed by
 #' Joe Swintek et al with CC0 license. It is not updated anymore and included
-#' for validation purpose. The modern replacement is [step_down_RSCABS()].
-#' 
-#' @details 
+#' for validation purpose. The modern replacement is [drcHelper::step_down_RSCABS()].
+#'
+#' @details
 #' This function is deprecated. For new analyses, please use the modern
-#' implementation in [step_down_RSCABS()] which provides:
+#' implementation in [drcHelper::step_down_RSCABS()] which provides:
 #' - Better error handling and input validation
-#' - More flexible data input formats  
+#' - More flexible data input formats
 #' - Improved statistical methodology
 #' - Better documentation and examples
 #'
@@ -51,11 +51,11 @@
 #' }
 runRSCABS <- function(Data,Treatment,Replicate='',Effects='',test.type='RS'){
   # Issue deprecation warning
-  .Deprecated("step_down_RSCABS", 
-              msg = paste("runRSCABS() is deprecated.", 
+  .Deprecated("step_down_RSCABS",
+              msg = paste("runRSCABS() is deprecated.",
                          "Please use step_down_RSCABS() for new code.",
                          "See ?step_down_RSCABS for the modern API."))
-  
+
   #This function will produce a table of step-down Cochran-Armitage trend tests with possible Rao-Scott adjustment by slices
   #It will Run the test on every effect in the Effect list
   #' @export