Fix #462 - capture KRI and other associated metadata

NAMESPACE

@@ -6,6 +6,7 @@ export(AE_Map_Adam)
 export(AE_Map_Raw)
 export(Analyze_Chisq)
 export(Analyze_Fisher)
+export(Analyze_Identity)
 export(Analyze_Poisson)
 export(Analyze_Poisson_PredictBounds)
 export(Analyze_Wilcoxon)

R/AE_Assess.R

@@ -14,6 +14,7 @@
 #'   `c(-5, 5)` for `strMethod` = "poisson" and `c(.0001, NA)` for `strMethod` = "wilcoxon".
 #' @param strMethod `character` Statistical model. Valid values include "poisson" (default) and
 #'  "wilcoxon".
+#' @param strKRILabel `character` Describe the `KRI` column, a vector of length 1 that defaults to `AEs/Week`
 #' @param lTags `list` Assessment tags, a named list of tags describing the assessment that defaults
 #'   to `list(Assessment="AE")`. `lTags` is returned as part of the assessment (`lAssess$lTags`) and
 #'   each tag is added as a column in `lAssess$dfSummary`.
@@ -52,6 +53,7 @@ AE_Assess <- function(
   dfInput,
   vThreshold = NULL,
   strMethod = "poisson",
+  strKRILabel = "AEs/Week",
   lTags = list(Assessment = "AE"),
   bChart = TRUE,
   bReturnChecks = FALSE,
@@ -61,7 +63,8 @@ AE_Assess <- function(
     "dfInput is not a data.frame" = is.data.frame(dfInput),
     "strMethod is not 'poisson' or 'wilcoxon'" = strMethod %in% c("poisson", "wilcoxon"),
     "One or more of these columns: SubjectID, SiteID, Count, Exposure, and Rate not found in dfInput" = all(c("SubjectID", "SiteID", "Count", "Exposure", "Rate") %in% names(dfInput)),
-    "strMethod must be length 1" = length(strMethod) == 1
+    "strMethod must be length 1" = length(strMethod) == 1,
+    "strKRILabel must be length 1" = length(strKRILabel) == 1
   )
 
   if (!is.null(lTags)) {
@@ -93,7 +96,7 @@ AE_Assess <- function(
     if (!bQuiet) cli::cli_h2("Initializing {.fn AE_Assess}")
     if (!bQuiet) cli::cli_text("Input data has {nrow(lAssess$dfInput)} rows.")
 
-    lAssess$dfTransformed <- gsm::Transform_EventCount(lAssess$dfInput, strCountCol = "Count", strExposureCol = "Exposure")
+    lAssess$dfTransformed <- gsm::Transform_EventCount(lAssess$dfInput, strCountCol = "Count", strExposureCol = "Exposure", strKRILabel = strKRILabel)
     if (!bQuiet) cli::cli_alert_success("{.fn Transform_EventCount} returned output with {nrow(lAssess$dfTransformed)} rows.")
 
     if (strMethod == "poisson") {
@@ -110,10 +113,10 @@ AE_Assess <- function(
       lAssess$dfAnalyzed <- gsm::Analyze_Poisson(lAssess$dfTransformed, bQuiet = bQuiet)
       if (!bQuiet) cli::cli_alert_success("{.fn Analyze_Poisson} returned output with {nrow(lAssess$dfAnalyzed)} rows.")
 
-      lAssess$dfFlagged <- gsm::Flag(lAssess$dfAnalyzed, strColumn = "Residuals", vThreshold = vThreshold)
+      lAssess$dfFlagged <- gsm::Flag(lAssess$dfAnalyzed, vThreshold = vThreshold)
       if (!bQuiet) cli::cli_alert_success("{.fn Flag} returned output with {nrow(lAssess$dfFlagged)} rows.")
 
-      lAssess$dfSummary <- gsm::Summarize(lAssess$dfFlagged, strScoreCol = "Residuals", lTags)
+      lAssess$dfSummary <- gsm::Summarize(lAssess$dfFlagged, lTags = lTags)
       if (!bQuiet) cli::cli_alert_success("{.fn Summarize} returned output with {nrow(lAssess$dfSummary)} rows.")
     } else if (strMethod == "wilcoxon") {
       if (is.null(vThreshold)) {
@@ -127,13 +130,13 @@ AE_Assess <- function(
         )
       }
 
-      lAssess$dfAnalyzed <- gsm::Analyze_Wilcoxon(lAssess$dfTransformed, "Rate", bQuiet = bQuiet)
+      lAssess$dfAnalyzed <- gsm::Analyze_Wilcoxon(lAssess$dfTransformed, bQuiet = bQuiet)
       if (!bQuiet) cli::cli_alert_success("{.fn Analyze_Wilcoxon} returned output with {nrow(lAssess$dfAnalyzed)} rows.")
 
-      lAssess$dfFlagged <- gsm::Flag(lAssess$dfAnalyzed, strColumn = "PValue", vThreshold = vThreshold, strValueColumn = "Estimate")
+      lAssess$dfFlagged <- gsm::Flag(lAssess$dfAnalyzed, vThreshold = vThreshold, strValueColumn = "Estimate")
       if (!bQuiet) cli::cli_alert_success("{.fn Flag} returned output with {nrow(lAssess$dfFlagged)} rows.")
 
-      lAssess$dfSummary <- gsm::Summarize(lAssess$dfFlagged, strScoreCol = "PValue", lTags = lTags)
+      lAssess$dfSummary <- gsm::Summarize(lAssess$dfFlagged, lTags = lTags)
       if (!bQuiet) cli::cli_alert_success("{.fn Summarize} returned output with {nrow(lAssess$dfSummary)} rows.")
     }
 

R/Analyze_Chisq.R

@@ -27,7 +27,7 @@
 #'
 #' @examples
 #' dfInput <- Disp_Map(dfDisp = safetyData::adam_adsl, strCol = "DCREASCD", strReason = "Adverse Event")
-#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count")
+#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strKRILabel = "Discontinuations due to AE/Month")
 #' dfAnalyzed <- Analyze_Chisq(dfTransformed)
 #'
 #' @import dplyr

R/Analyze_Fisher.R

@@ -26,7 +26,7 @@
 #'
 #' @examples
 #' dfInput <- Disp_Map(dfDisp = safetyData::adam_adsl, strCol = "DCREASCD", strReason = "Adverse Event")
-#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count")
+#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strKRILabel = "Discontinuations due to AE")
 #' dfAnalyzed <- Analyze_Fisher(dfTransformed)
 #'
 #' @import dplyr

R/Analyze_Identity.R

@@ -0,0 +1,31 @@
+#' Analyze Identity
+#'
+#' Used in the data pipeline between `Transform` and `Flag` to rename KRI and Score columns.
+#'
+#' @param dfTransformed `data.frame` created by `Transform_EventCount()`
+#' @param strValueCol `character` Name of column that will be copied as `Score`
+#' @param strLabelCol `character` Name of column that will be copied as `ScoreLabel`
+#' @param bQuiet `logical` Suppress warning messages? Default: `TRUE`
+#'
+#' @return `data.frame` that adds two columns to `dfTransformed`: `Score` and `ScoreLabel`
+#'
+#' @export
+
+Analyze_Identity <- function(dfTransformed, strValueCol = 'KRI', strLabelCol = "KRILabel", bQuiet = TRUE){
+
+  stopifnot(
+    "dfTransformed is not a data.frame" = is.data.frame(dfTransformed),
+    "strValueCol and/or strLabelCol not found in dfTransformed" = all(c(strValueCol, strLabelCol) %in% names(dfTransformed)),
+    "strValueCol must be length 1" = length(strValueCol) == 1,
+    "strLabelCol must be length 1" = length(strLabelCol) == 1
+  )
+
+  dfAnalyzed <- dfTransformed %>%
+    mutate(Score = .data[[strValueCol]],
+           ScoreLabel = .data[[strLabelCol]])
+
+  if(!bQuiet) cli::cli_text(paste0("{.var Score} column created from `", strValueCol, "`."))
+  if(!bQuiet) cli::cli_text(paste0("{.var ScoreLabel} column created from `", strLabelCol, "`."))
+
+  return(dfAnalyzed)
+}

R/Analyze_Poisson.R

@@ -24,7 +24,7 @@
 #'
 #' @examples
 #' dfInput <- AE_Map_Raw()
-#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strExposureCol = "Exposure")
+#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strExposureCol = "Exposure", strKRILabel = "AEs/Week")
 #' dfAnalyzed <- Analyze_Poisson(dfTransformed)
 #'
 #' @import dplyr
@@ -38,7 +38,8 @@
 Analyze_Poisson <- function(dfTransformed, bQuiet = TRUE) {
   stopifnot(
     "dfTransformed is not a data.frame" = is.data.frame(dfTransformed),
-    "One or more of these columns: SiteID, N, TotalExposure, TotalCount, Rate" = all(c("SiteID", "N", "TotalExposure", "TotalCount", "Rate") %in% names(dfTransformed)),
+    "One or more of these columns not found: SiteID, N, TotalExposure, TotalCount, KRI, KRILabel" =
+      all(c("SiteID", "N", "TotalExposure", "TotalCount", "KRI", "KRILabel") %in% names(dfTransformed)),
     "NA value(s) found in SiteID" = all(!is.na(dfTransformed[["SiteID"]]))
   )
 
@@ -60,12 +61,21 @@ Analyze_Poisson <- function(dfTransformed, bQuiet = TRUE) {
   )
 
   dfAnalyzed <- broom::augment(cModel, dfModel, type.predict = "response") %>%
-    rename(
-      Residuals = .data$.resid,
-      PredictedCount = .data$.fitted,
+    mutate(
+      ScoreLabel = "Residuals"
     ) %>%
-    select(.data$SiteID, .data$N, .data$TotalExposure, .data$TotalCount, .data$Rate, .data$Residuals, .data$PredictedCount) %>%
-    arrange(.data$Residuals)
+    select(
+      .data$SiteID,
+      .data$N,
+      .data$TotalCount,
+      .data$TotalExposure,
+      .data$KRI,
+      .data$KRILabel,
+      Score = .data$.resid,
+      .data$ScoreLabel,
+      PredictedCount = .data$.fitted
+      ) %>%
+    arrange(.data$Score)
 
   return(dfAnalyzed)
 }

R/Analyze_Poisson_PredictBounds.R

@@ -30,7 +30,7 @@
 #'
 #' @examples
 #' dfInput <- AE_Map_Adam()
-#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strExposureCol = "Exposure")
+#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strExposureCol = "Exposure", strKRILabel = "AEs/Week")
 #' dfBounds <- Analyze_Poisson_PredictBounds(dfTransformed, c(-5, 5))
 #'
 #' @importFrom stats glm offset poisson qchisq

R/Analyze_Wilcoxon.R

@@ -29,8 +29,8 @@
 #'
 #' @examples
 #' dfInput <- AE_Map_Raw()
-#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strExposureCol = "Exposure")
-#' dfAnalyzed <- Analyze_Wilcoxon(dfTransformed, strOutcomeCol = "Rate")
+#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strExposureCol = "Exposure", strKRILabel = "AEs/Week")
+#' dfAnalyzed <- Analyze_Wilcoxon(dfTransformed)
 #'
 #' @import dplyr
 #' @importFrom broom glance
@@ -44,7 +44,7 @@
 
 Analyze_Wilcoxon <- function(
   dfTransformed,
-  strOutcomeCol = NULL,
+  strOutcomeCol = "KRI",
   strPredictorCol = "SiteID",
   bQuiet = TRUE
 ) {
@@ -62,7 +62,9 @@ Analyze_Wilcoxon <- function(
     "@param:strOutcomeCol or @param:strPredictorCol not found in @param:dfTransformed" =
       all(c(strPredictorCol, strOutcomeCol) %in% names(dfTransformed)),
     "NA value(s) found in @param:strPredictorCol" =
-      all(!is.na(dfTransformed[[strPredictorCol]]))
+      all(!is.na(dfTransformed[[strPredictorCol]])),
+    "One or more of these columns not found: SiteID, N, TotalExposure, TotalCount, KRI, KRILabel" =
+      all(c("SiteID", "N", "TotalExposure", "TotalCount", "KRI", "KRILabel") %in% names(dfTransformed))
   )
 
   wilcoxon_model <- function(predictorValue) {
@@ -126,6 +128,9 @@ Analyze_Wilcoxon <- function(
 
   return(
     dfAnalyzed %>%
-      select(names(dfTransformed), .data$Estimate, .data$PValue)
+      select(names(dfTransformed), .data$Estimate, Score = .data$PValue) %>%
+      mutate(
+        ScoreLabel = "P value"
+          )
   )
 }

R/Consent_Assess.R

@@ -24,6 +24,7 @@
 #' @param dfInput `data.frame` Input data, a data frame with one record per subject.
 #' @param nThreshold `numeric` Threshold specification. Default: `0.5`
 #' @param lTags `list` Assessment tags, a named list of tags describing the assessment that defaults to `list(Assessment="IE")`. `lTags` is returned as part of the assessment (`lAssess$lTags`) and each tag is added as a column in `lAssess$dfSummary`.
+#' @param strKRILabel `character` Describe the `KRI` column, a vector of length 1 that defaults to `Total Number of Consent Issues`
 #' @param bChart `logical` Generate data visualization? Default: `TRUE`
 #' @param bReturnChecks `logical` Return input checks from `is_mapping_valid`? Default: `FALSE`
 #' @param bQuiet `logical` Suppress warning messages? Default: `TRUE`
@@ -57,6 +58,7 @@ Consent_Assess <- function(
   dfInput,
   nThreshold = 0.5,
   lTags = list(Assessment = "Consent"),
+  strKRILabel = "Total Number of Consent Issues",
   bChart = TRUE,
   bReturnChecks = FALSE,
   bQuiet = TRUE
@@ -65,7 +67,8 @@ Consent_Assess <- function(
     "dfInput is not a data.frame" = is.data.frame(dfInput),
     "One or more of these columns: SubjectID, SiteID,and Count not found in dfInput" = all(c("SubjectID", "SiteID", "Count") %in% names(dfInput)),
     "nThreshold must be numeric" = is.numeric(nThreshold),
-    "nThreshold must be length 1" = length(nThreshold) == 1
+    "nThreshold must be length 1" = length(nThreshold) == 1,
+    "strKRILabel must be length 1" = length(strKRILabel) == 1
   )
 
   if (!is.null(lTags)) {
@@ -96,16 +99,18 @@ Consent_Assess <- function(
   if (checks$status) {
     if (!bQuiet) cli::cli_h2("Initializing {.fn Consent_Assess}")
     if (!bQuiet) cli::cli_text("Input data has {nrow(lAssess$dfInput)} rows.")
-    lAssess$dfTransformed <- gsm::Transform_EventCount(lAssess$dfInput, strCountCol = "Count")
+    lAssess$dfTransformed <- gsm::Transform_EventCount(lAssess$dfInput, strCountCol = "Count", strKRILabel = strKRILabel)
     if (!bQuiet) cli::cli_alert_success("{.fn Transform_EventCount} returned output with {nrow(lAssess$dfTransformed)} rows.")
 
-    lAssess$dfAnalyzed <- lAssess$dfTransformed %>% dplyr::mutate(Estimate = .data$TotalCount)
-    if (!bQuiet) cli::cli_alert_info("No analysis function used. {.var dfTransformed} copied directly to {.var dfAnalyzed}")
+    lAssess$dfAnalyzed <- lAssess$dfTransformed %>%
+      Analyze_Identity(bQuiet = bQuiet)
 
-    lAssess$dfFlagged <- gsm::Flag(lAssess$dfAnalyzed, vThreshold = c(NA, nThreshold), strColumn = "Estimate")
+    if (!bQuiet) cli::cli_alert_info("No analysis function used. {.var dfTransformed} copied directly to {.var dfAnalyzed} with added {.var ScoreLabel} column.")
+
+    lAssess$dfFlagged <- gsm::Flag(lAssess$dfAnalyzed, vThreshold = c(NA, nThreshold))
     if (!bQuiet) cli::cli_alert_success("{.fn Flag} returned output with {nrow(lAssess$dfFlagged)} rows.")
 
-    lAssess$dfSummary <- gsm::Summarize(lAssess$dfFlagged, strScoreCol = "TotalCount", lTags)
+    lAssess$dfSummary <- gsm::Summarize(lAssess$dfFlagged, lTags = lTags)
     if (!bQuiet) cli::cli_alert_success("{.fn Summarize} returned output with {nrow(lAssess$dfSummary)} rows.")
 
     if (bChart) {

R/Flag.R

@@ -32,12 +32,12 @@
 #'
 #' @examples
 #' dfInput <- AE_Map_Adam()
-#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strExposureCol = "Exposure")
-#' dfAnalyzed <- Analyze_Wilcoxon(dfTransformed, "Rate")
-#' dfFlagged <- Flag(dfAnalyzed) # PValue < 0.05 flagged
+#' dfTransformed <- Transform_EventCount(dfInput, strCountCol = "Count", strExposureCol = "Exposure", strKRILabel = "AEs/Week")
+#' dfAnalyzed <- Analyze_Wilcoxon(dfTransformed)
+#' dfFlagged <- Flag(dfAnalyzed) # P value (dfAnalyzed$Score) < 0.05 flagged
 #' dfFlagged10 <- Flag(dfAnalyzed, vThreshold = c(0.10, NA)) # PValue <0.10 flagged
 #' # Flag direction set based on 'Statistic' column
-#' dfFlagged <- Flag(dfAnalyzed, strColumn = "PValue", strValueColumn = "Estimate")
+#' dfFlagged <- Flag(dfAnalyzed, strColumn = "Score", strValueColumn = "Estimate")
 #'
 #' @import dplyr
 #' @importFrom stats median
@@ -46,7 +46,7 @@
 
 Flag <- function(
   dfAnalyzed,
-  strColumn = "PValue",
+  strColumn = "Score",
   vThreshold = c(0.05, NA),
   strValueColumn = NULL
 ) {

R/IE_Assess.R

@@ -14,6 +14,7 @@
 #' @param dfInput `data.frame` Input data, a data frame with one record per subject.
 #' @param nThreshold `numeric` Threshold specification. Default: `0.5`
 #' @param lTags `list` Assessment tags, a named list of tags describing the assessment that defaults to `list(Assessment="IE")`. `lTags` is returned as part of the assessment (`lAssess$lTags`) and each tag is added as a column in `lAssess$dfSummary`.
+#' @param strKRILabel `character` Describe the `KRI` column, a vector of length 1 that defaults to `# of Inclusion/Exclusion Issues`
 #' @param bChart `logical` Generate data visualization? Default: `TRUE`
 #' @param bReturnChecks `logical` Return input checks from `is_mapping_valid`? Default: `FALSE`
 #' @param bQuiet `logical` Suppress warning messages? Default: `TRUE`
@@ -48,6 +49,7 @@ IE_Assess <- function(
   dfInput,
   nThreshold = 0.5,
   lTags = list(Assessment = "IE"),
+  strKRILabel = "# of Inclusion/Exclusion Issues",
   bChart = TRUE,
   bReturnChecks = FALSE,
   bQuiet = TRUE
@@ -56,7 +58,8 @@ IE_Assess <- function(
     "dfInput is not a data.frame" = is.data.frame(dfInput),
     "One or more of these columns: SubjectID, SiteID, Count, Exposure, and Rate not found in dfInput" = all(c("SubjectID", "SiteID", "Count") %in% names(dfInput)),
     "nThreshold must be numeric" = is.numeric(nThreshold),
-    "nThreshold must be length 1" = length(nThreshold) == 1
+    "nThreshold must be length 1" = length(nThreshold) == 1,
+    "strKRILabel must be length 1" = length(strKRILabel) == 1
   )
 
   if (!is.null(lTags)) {
@@ -87,16 +90,18 @@ IE_Assess <- function(
   if (checks$status) {
     if (!bQuiet) cli::cli_h2("Initializing {.fn IE_Assess}")
     if (!bQuiet) cli::cli_text("Input data has {nrow(lAssess$dfInput)} rows.")
-    lAssess$dfTransformed <- gsm::Transform_EventCount(lAssess$dfInput, strCountCol = "Count")
+    lAssess$dfTransformed <- gsm::Transform_EventCount(lAssess$dfInput, strCountCol = "Count", strKRILabel = strKRILabel)
     if (!bQuiet) cli::cli_alert_success("{.fn Transform_EventCount} returned output with {nrow(lAssess$dfTransformed)} rows.")
 
-    lAssess$dfAnalyzed <- lAssess$dfTransformed %>% dplyr::mutate(Estimate = .data$TotalCount)
-    if (!bQuiet) cli::cli_alert_info("No analysis function used. {.var dfTransformed} copied directly to {.var dfAnalyzed}")
+    lAssess$dfAnalyzed <- lAssess$dfTransformed %>%
+      Analyze_Identity(bQuiet = bQuiet)
 
-    lAssess$dfFlagged <- gsm::Flag(lAssess$dfAnalyzed, vThreshold = c(NA, nThreshold), strColumn = "Estimate")
+    if (!bQuiet) cli::cli_alert_info("No analysis function used. {.var dfTransformed} copied directly to {.var dfAnalyzed} with added {.var ScoreLabel} column.")
+
+    lAssess$dfFlagged <- gsm::Flag(lAssess$dfAnalyzed, vThreshold = c(NA, nThreshold))
     if (!bQuiet) cli::cli_alert_success("{.fn Flag} returned output with {nrow(lAssess$dfFlagged)} rows.")
 
-    lAssess$dfSummary <- gsm::Summarize(lAssess$dfFlagged, strScoreCol = "TotalCount", lTags)
+    lAssess$dfSummary <- gsm::Summarize(lAssess$dfFlagged, lTags = lTags)
     if (!bQuiet) cli::cli_alert_success("{.fn Summarize} returned output with {nrow(lAssess$dfSummary)} rows.")
 
     if (bChart) {