diff --git a/R/AE_Assess.R b/R/AE_Assess.R
index cbd5f3b8a..e375a71a3 100644
--- a/R/AE_Assess.R
+++ b/R/AE_Assess.R
@@ -25,10 +25,10 @@
 #' @return `list` `lData`, a named list with:
 #' - each data frame in the data pipeline
 #'   - `dfTransformed`, returned by [gsm::Transform_EventCount()]
-#'   - `dfAnalyzed`, returned by [gsm::Analyze_Poisson()] or [gsm::Analyze_Wilcoxon()]
+#'   - `dfAnalyzed`, returned by [gsm::Analyze_Poisson()], [gsm::Analyze_Wilcoxon()], or [gsm::Analyze_Identity()]
 #'   - `dfFlagged`, returned by [gsm::Flag()]
 #'   - `dfSummary`, returned by [gsm::Summarize()]
-#'   - `dfBounds`, returned by [gsm::Analyze_Poisson_PredictBounds()] when strMethod == 'poisson'
+#'   - `dfBounds`, returned by [gsm::Analyze_Poisson_PredictBounds()] only when strMethod == 'poisson'
 #' - `list` `lCharts`, a named list with:
 #'   - `scatter`, a ggplot2 object returned by [gsm::Visualize_Scatter()]
 #'   - `barMetric`, a ggplot2 object returned by [gsm::Visualize_Score()] using strType == "metric"
@@ -48,7 +48,6 @@
 #' ae_assessment_wilcoxon <- AE_Assess(dfInput, strMethod = "wilcoxon")
 #'
 #' @importFrom cli cli_alert_success cli_alert_warning cli_h2 cli_text
-#' @importFrom purrr map map_dbl
 #' @importFrom yaml read_yaml
 #' @importFrom glue glue
 #'
@@ -60,6 +59,8 @@ AE_Assess <- function(dfInput,
   lMapping =  yaml::read_yaml(system.file("mappings", "AE_Assess.yaml", package = "gsm")),
   strGroup = "Site",
   bQuiet = TRUE) {
+
+# data checking -----------------------------------------------------------
   stopifnot(
     "strMethod is not 'poisson', 'wilcoxon', or 'identity'" = strMethod %in% c("poisson", "wilcoxon", "identity"),
     "strMethod must be length 1" = length(strMethod) == 1,
@@ -67,7 +68,6 @@ AE_Assess <- function(dfInput,
     "bQuiet must be logical" = is.logical(bQuiet)
   )
 
-
   lMapping$dfInput$strGroupCol <- lMapping$dfInput[[glue::glue("str{strGroup}Col")]]
 
   lChecks <- CheckInputs(
@@ -78,7 +78,7 @@ AE_Assess <- function(dfInput,
   )
 
 
-# set vThreshold if NULL ------------------------------------------------
+# set thresholds and flagging parameters ----------------------------------
   if (is.null(vThreshold)) {
     vThreshold <- switch(
       strMethod,
@@ -88,6 +88,15 @@ AE_Assess <- function(dfInput,
     )
   }
 
+  strValueColumnVal <- switch(
+    strMethod,
+    poisson = NULL,
+    wilcoxon = "Estimate",
+    identity = "Score"
+  )
+
+
+# begin running assessment ------------------------------------------------
   if (!lChecks$status) {
     if (!bQuiet) cli::cli_alert_warning("{.fn AE_Assess} did not run because of failed check.")
     return(list(
@@ -98,10 +107,8 @@ AE_Assess <- function(dfInput,
   }else{
     if (!bQuiet) cli::cli_h2("Initializing {.fn AE_Assess}")
 
-    ########################################
-    ## Save Data pipeline results to lData
-    ########################################
 
+# dfTransformed -----------------------------------------------------------
     if (!bQuiet) cli::cli_text("Input data has {nrow(dfInput)} rows.")
     lData <- list()
     lData$dfTransformed <- gsm::Transform_Rate(
@@ -113,7 +120,8 @@ AE_Assess <- function(dfInput,
     if (!bQuiet) cli::cli_alert_success("{.fn Transform_Rate} returned output with {nrow(lData$dfTransformed)} rows.")
 
 
-# refactor to only analyze in elseif --------------------------------------
+
+# dfAnalyzed --------------------------------------------------------------
     if (strMethod == "poisson") {
       lData$dfAnalyzed <- gsm::Analyze_Poisson(lData$dfTransformed, bQuiet = bQuiet)
       if (!bQuiet) cli::cli_alert_success("{.fn Analyze_Poisson} returned output with {nrow(lData$dfAnalyzed)} rows.")
@@ -127,26 +135,18 @@ AE_Assess <- function(dfInput,
     }
 
 
-# only parameter changed for Flag is strValueCol --------------------------
-    strValueColumnVal <- switch(
-      strMethod,
-      poisson = NULL,
-      wilcoxon = "Estimate",
-      identity = "Score"
-    )
 
+# dfFlagged ---------------------------------------------------------------
     lData$dfFlagged <- gsm::Flag(lData$dfAnalyzed, vThreshold = vThreshold, strValueColumn = strValueColumnVal)
     if (!bQuiet) cli::cli_alert_success("{.fn Flag} returned output with {nrow(lData$dfFlagged)} rows.")
 
+
+# dfSummary ---------------------------------------------------------------
     lData$dfSummary <- gsm::Summarize(lData$dfFlagged)
     if (!bQuiet) cli::cli_alert_success("{.fn Summarize} returned output with {nrow(lData$dfSummary)} rows.")
 
-    ########################################
-    ## Save Charts to lCharts
-    ##
-    ## - strGroupLabel defaults to strGroup for now
-    ## - may want to move this out to be more flexible
-    ########################################
+
+# visualizations ----------------------------------------------------------
     lCharts <- list()
 
     if(!hasName(lData, 'dfBounds')) lData$dfBounds <- NULL
@@ -160,6 +160,8 @@ AE_Assess <- function(dfInput,
     lCharts$barScore <- Visualize_Score(dfFlagged = lData$dfFlagged, strType = "score", vThreshold = vThreshold)
     if (!bQuiet) cli::cli_alert_success("{.fn Visualize_Score} created a chart.")
 
+
+# return data -------------------------------------------------------------
     return(list(
       lData = lData,
       lCharts = lCharts,
diff --git a/R/PD_Assess.R b/R/PD_Assess.R
index 22203b0de..fff1abc19 100644
--- a/R/PD_Assess.R
+++ b/R/PD_Assess.R
@@ -17,27 +17,26 @@
 #'   - `"poisson"` (default)
 #'   - `"wilcoxon"`
 #'   - `"identity"`
-#' @param strKRILabel `character` KRI description. Default: `"PDs/Week"`
+#' @param lMapping Column metadata with structure `domain$key`, where `key` contains the name
 #' @param strGroup `character` Grouping variable. `"Site"` (the default) uses the column named in `mapping$strSiteCol`. Other valid options using the default mapping are `"Study"` and `"CustomGroup"`.
-#' @param lTags `list` Assessment tags, a named list of tags describing the assessment that defaults
-#'   to `list(Assessment = "PD")`. `lTags` is returned as part of the assessment (`lAssess$lTags`)
-#'   and each tag is added as a column in `lAssess$dfSummary`.
-#' @param bChart `logical` Generate data visualization? Default: `TRUE`
-#' @param bReturnChecks `logical` Return input checks from [gsm::is_mapping_valid()]? Default: `FALSE`
 #' @param bQuiet `logical` Suppress warning messages? Default: `TRUE`
 #'
-#' @return `list` Assessment, a named list with:
+#' @return `list` `lData`, a named list with:
 #' - each data frame in the data pipeline
-#'   - `dfInput`
 #'   - `dfTransformed`, returned by [gsm::Transform_EventCount()]
-#'   - `dfAnalyzed`, returned by [gsm::Analyze_Poisson()] or [gsm::Analyze_Wilcoxon()]
+#'   - `dfAnalyzed`, returned by [gsm::Analyze_Poisson()], [gsm::Analyze_Wilcoxon()], or [gsm::Analyze_Identity()]
 #'   - `dfFlagged`, returned by [gsm::Flag()]
 #'   - `dfSummary`, returned by [gsm::Summarize()]
-#' - assessment metadata
-#'   - `strFunctionName`
-#'   - `lTags`
-#' - output(s)
-#'   - `chart`
+#'   - `dfBounds`, returned by [gsm::Analyze_Poisson_PredictBounds()] only when strMethod == 'poisson'
+#' - `list` `lCharts`, a named list with:
+#'   - `scatter`, a ggplot2 object returned by [gsm::Visualize_Scatter()]
+#'   - `barMetric`, a ggplot2 object returned by [gsm::Visualize_Score()] using strType == "metric"
+#'   - `barScore`, a ggplot2 object returned by [gsm::Visualize_Score()] using strType == "score"
+#' - `list` `lChecks`, a named list with:
+#'   - `dfInput`, a named list returned by [gsm::is_mapping_valid()]
+#'   - `status`, a boolean returned by [gsm::is_mapping_valid()]
+#'   - `mapping`, a named list that is provided as an argument to the `lMapping` parameter in [gsm::AE_Assess()]
+#'   - `spec`, a named list used to define variable specifications
 #'
 #' @includeRmd ./man/md/PD_Assess.md
 #' @includeRmd ./man/md/analyze_rate.md
@@ -48,7 +47,6 @@
 #' pd_assessment_wilcoxon <- PD_Assess(dfInput, strMethod = "wilcoxon")
 #'
 #' @importFrom cli cli_alert_success cli_alert_warning cli_h2 cli_text
-#' @importFrom purrr map map_dbl
 #' @importFrom yaml read_yaml
 #' @importFrom glue glue
 #'
@@ -57,154 +55,113 @@
 PD_Assess <- function(dfInput,
   vThreshold = NULL,
   strMethod = "poisson",
-  strKRILabel = "PDs/Week",
+  lMapping = yaml::read_yaml(system.file("mappings", "PD_Assess.yaml", package = "gsm")),
   strGroup = "Site",
-  lTags = list(Assessment = "PD"),
-  bChart = TRUE,
-  bReturnChecks = FALSE,
   bQuiet = TRUE) {
+
+# data checking -----------------------------------------------------------
   stopifnot(
-    "dfInput is not a data.frame" = is.data.frame(dfInput),
-    "dfInput is missing one or more of these columns: SubjectID, Count, Exposure, and Rate" = all(c("SubjectID", "Count", "Exposure", "Rate") %in% names(dfInput)),
     "strMethod is not 'poisson', 'wilcoxon', or 'identity'" = strMethod %in% c("poisson", "wilcoxon", "identity"),
     "strMethod must be length 1" = length(strMethod) == 1,
-    "strKRILabel must be length 1" = length(strKRILabel) == 1,
     "strGroup must be one of: Site, Study, or CustomGroup" = strGroup %in% c("Site", "Study", "CustomGroup"),
-    "bChart must be logical" = is.logical(bChart),
-    "bReturnChecks must be logical" = is.logical(bReturnChecks),
     "bQuiet must be logical" = is.logical(bQuiet)
   )
 
-  if (!is.null(lTags)) {
-    stopifnot(
-      "lTags is not named" = (!is.null(names(lTags))),
-      "lTags has unnamed elements" = all(names(lTags) != ""),
-      "lTags cannot contain elements named: 'GroupID', 'GroupLabel', 'N', 'KRI', 'KRILabel', 'Score', 'ScoreLabel', or 'Flag'" = !names(lTags) %in%
-        c(
-          "GroupID",
-          "GroupLabel",
-          "N",
-          "KRI",
-          "KRILabel",
-          "Score",
-          "ScoreLabel",
-          "Flag"
-        )
-    )
-
-    if (any(unname(purrr::map_dbl(lTags, ~ length(.))) > 1)) {
-      lTags <- purrr::map(lTags, ~ paste(.x, collapse = ", "))
-    }
-  }
+  lMapping$dfInput$strGroupCol <- lMapping$dfInput[[glue::glue("str{strGroup}Col")]]
 
-  lAssess <- list(
-    strFunctionName = deparse(sys.call()[1]),
-    lTags = lTags,
-    dfInput = dfInput
+  lChecks <- CheckInputs(
+    context = "PD_Assess",
+    dfs = list(dfInput = dfInput),
+    mapping = lMapping,
+    bQuiet = bQuiet
   )
 
-  mapping <- yaml::read_yaml(system.file("mappings", "AE_Assess.yaml", package = "gsm"))
-  mapping$dfInput$strGroupCol <- mapping$dfInput[[glue::glue("str{strGroup}Col")]]
+# set thresholds and flagging parameters ----------------------------------
+  if (is.null(vThreshold)) {
+    vThreshold <- switch(
+      strMethod,
+      poisson = c(-5, 5),
+      wilcoxon = c(0.0001, NA),
+      identity = c(0.000895, 0.003059)
+    )
+  }
 
-  stopifnot(
-    "`strGroup` not found in mapping" = glue::glue("str{strGroup}Col") %in% names(mapping$dfInput),
-    "`strGroupCol` not found in dfInput" = mapping$dfInput$strGroupCol %in% names(dfInput)
+  strValueColumnVal <- switch(
+    strMethod,
+    poisson = NULL,
+    wilcoxon = "Estimate",
+    identity = "Score"
   )
 
-  checks <- CheckInputs(
-    context = "PD_Assess",
-    dfs = list(dfInput = lAssess$dfInput),
-    mapping = mapping,
-    bQuiet = bQuiet
-  )
 
-  if (checks$status) {
+# begin running assessment ------------------------------------------------
+  if (!lChecks$status) {
+    if (!bQuiet) cli::cli_alert_warning("{.fn PD_Assess} did not run because of failed check.")
+    return(list(
+      lData = NULL,
+      lCharts = NULL,
+      lChecks = lChecks
+    ))
+  } else {
     if (!bQuiet) cli::cli_h2("Initializing {.fn PD_Assess}")
-    if (!bQuiet) cli::cli_text("Input data has {nrow(lAssess$dfInput)} rows.")
-
-    lAssess$dfTransformed <- gsm::Transform_EventCount(
-      lAssess$dfInput,
-      strGroupCol = mapping$dfInput$strGroupCol,
-      strCountCol = "Count",
-      strExposureCol = "Exposure",
-      strKRILabel = strKRILabel
+
+# dfTransformed -----------------------------------------------------------
+    if (!bQuiet) cli::cli_text("Input data has {nrow(dfInput)} rows.")
+    lData <- list()
+
+    lData$dfTransformed <- gsm::Transform_Rate(
+      dfInput = dfInput,
+      strGroupCol = lMapping$dfInput$strGroupCol,
+      strNumeratorCol = "Count",
+      strDenominatorCol = "Exposure"
     )
-    if (!bQuiet) cli::cli_alert_success("{.fn Transform_EventCount} returned output with {nrow(lAssess$dfTransformed)} rows.")
+    if (!bQuiet) cli::cli_alert_success("{.fn Transform_Rate} returned output with {nrow(lData$dfTransformed)} rows.")
 
+
+# dfAnalyzed --------------------------------------------------------------
     if (strMethod == "poisson") {
-      if (is.null(vThreshold)) {
-        vThreshold <- c(-5, 5)
-      } else {
-        stopifnot(
-          "vThreshold is not numeric" = is.numeric(vThreshold),
-          "vThreshold for Poisson contains NA values" = all(!is.na(vThreshold)),
-          "vThreshold is not length 2" = length(vThreshold) == 2
-        )
-      }
-
-      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$dfAnalyzed, vThreshold = vThreshold)
-      if (!bQuiet) cli::cli_alert_success("{.fn Flag} returned output with {nrow(lAssess$dfFlagged)} rows.")
-
-      lAssess$dfSummary <- gsm::Summarize(lAssess$dfFlagged, lTags = lTags)
-      if (!bQuiet) cli::cli_alert_success("{.fn Summarize} returned output with {nrow(lAssess$dfSummary)} rows.")
+      lData$dfAnalyzed <- gsm::Analyze_Poisson(lData$dfTransformed, bQuiet = bQuiet)
+      if (!bQuiet) cli::cli_alert_success("{.fn Analyze_Poisson} returned output with {nrow(lData$dfAnalyzed)} rows.")
+      lData$dfBounds <- gsm::Analyze_Poisson_PredictBounds(lData$dfTransformed, vThreshold = vThreshold, bQuiet = bQuiet)
     } else if (strMethod == "wilcoxon") {
-      if (is.null(vThreshold)) {
-        vThreshold <- c(0.0001, NA)
-      } else {
-        stopifnot(
-          "vThreshold is not numeric" = is.numeric(vThreshold),
-          "Lower limit (first element) for Wilcoxon vThreshold is not between 0 and 1" = vThreshold[1] < 1 & vThreshold[1] > 0,
-          "Upper limit (second element) for Wilcoxon vThreshold is not NA" = is.na(vThreshold[2]),
-          "vThreshold is not length 2" = length(vThreshold) == 2
-        )
-      }
-
-      lAssess$dfAnalyzed <- gsm::Analyze_Wilcoxon(lAssess$dfTransformed, "KRI", bQuiet = bQuiet)
-      if (!bQuiet) cli::cli_alert_success("{.fn Analyze_Wilcoxon} returned output with {nrow(lAssess$dfAnalyzed)} rows.")
-
-      lAssess$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, lTags = lTags)
-      if (!bQuiet) cli::cli_alert_success("{.fn Summarize} returned output with {nrow(lAssess$dfSummary)} rows.")
+      lData$dfAnalyzed <- gsm::Analyze_Wilcoxon(lData$dfTransformed, bQuiet = bQuiet)
+      if (!bQuiet) cli::cli_alert_success("{.fn Analyze_Wilcoxon} returned output with {nrow(lData$dfAnalyzed)} rows.")
     } else if (strMethod == "identity") {
-      if (is.null(vThreshold)) {
-        vThreshold <- c(0.000895, 0.003059)
-      } else {
-        stopifnot(
-          "vThreshold is not numeric" = is.numeric(vThreshold),
-          "vThreshold for Identity contains NA values" = all(!is.na(vThreshold)),
-          "vThreshold is not length 2" = length(vThreshold) == 2
-        )
-      }
-
-      lAssess$dfAnalyzed <- gsm::Analyze_Identity(lAssess$dfTransformed, bQuiet = bQuiet)
-      if (!bQuiet) cli::cli_alert_success("{.fn Analyze_Identity} returned output with {nrow(lAssess$dfAnalyzed)} rows.")
-
-      lAssess$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, lTags = lTags)
-      if (!bQuiet) cli::cli_alert_success("{.fn Summarize} returned output with {nrow(lAssess$dfSummary)} rows.")
+      lData$dfAnalyzed <- gsm::Analyze_Identity(lData$dfTransformed)
+      if (!bQuiet) cli::cli_alert_success("{.fn Analyze_Identity} returned output with {nrow(lData$dfAnalyzed)} rows.")
     }
 
-    if (bChart) {
-      if (strMethod == "poisson") {
-        lAssess$dfBounds <- gsm::Analyze_Poisson_PredictBounds(lAssess$dfTransformed, vThreshold = vThreshold, bQuiet = bQuiet)
-        lAssess$chart <- gsm::Visualize_Scatter(lAssess$dfFlagged, lAssess$dfBounds)
-        if (!bQuiet) cli::cli_alert_success("{.fn Visualize_Scatter} created a chart.")
-      } else {
-        lAssess$chart <- gsm::Visualize_Scatter(lAssess$dfFlagged)
-        if (!bQuiet) cli::cli_alert_success("{.fn Visualize_Scatter} created a chart.")
-      }
-    }
-  } else {
-    if (!bQuiet) cli::cli_alert_warning("{.fn PD_Assess} did not run because of failed check.")
-  }
 
-  if (bReturnChecks) lAssess$lChecks <- checks
-  return(lAssess)
+# dfFlagged ---------------------------------------------------------------
+    lData$dfFlagged <- gsm::Flag(lData$dfAnalyzed, vThreshold = vThreshold, strValueColumn = strValueColumnVal)
+    if (!bQuiet) cli::cli_alert_success("{.fn Flag} returned output with {nrow(lData$dfFlagged)} rows.")
+
+
+# dfSummary ---------------------------------------------------------------
+    lData$dfSummary <- gsm::Summarize(lData$dfFlagged)
+    if (!bQuiet) cli::cli_alert_success("{.fn Summarize} returned output with {nrow(lData$dfSummary)} rows.")
+
+
+# visualizations ----------------------------------------------------------
+    lCharts <- list()
+
+    if(!hasName(lData, 'dfBounds')) lData$dfBounds <- NULL
+
+    lCharts$scatter <- gsm::Visualize_Scatter(dfFlagged = lData$dfFlagged, dfBounds = lData$dfBounds, strGroupLabel = strGroup)
+    if (!bQuiet) cli::cli_alert_success("{.fn Visualize_Scatter} created a chart.")
+
+    lCharts$barMetric <- Visualize_Score(dfFlagged = lData$dfFlagged, strType = "metric")
+    if (!bQuiet) cli::cli_alert_success("{.fn Visualize_Score} created a chart.")
+
+    lCharts$barScore <- Visualize_Score(dfFlagged = lData$dfFlagged, strType = "score", vThreshold = vThreshold)
+    if (!bQuiet) cli::cli_alert_success("{.fn Visualize_Score} created a chart.")
+
+
+# return data -------------------------------------------------------------
+    return(list(
+      lData = lData,
+      lCharts = lCharts,
+      lChecks = lChecks
+    ))
+  }
 }
diff --git a/man/AE_Assess.Rd b/man/AE_Assess.Rd
index bdfad019d..93b2de069 100644
--- a/man/AE_Assess.Rd
+++ b/man/AE_Assess.Rd
@@ -40,10 +40,10 @@ of the column.}
 \item each data frame in the data pipeline
 \itemize{
 \item \code{dfTransformed}, returned by \code{\link[=Transform_EventCount]{Transform_EventCount()}}
-\item \code{dfAnalyzed}, returned by \code{\link[=Analyze_Poisson]{Analyze_Poisson()}} or \code{\link[=Analyze_Wilcoxon]{Analyze_Wilcoxon()}}
+\item \code{dfAnalyzed}, returned by \code{\link[=Analyze_Poisson]{Analyze_Poisson()}}, \code{\link[=Analyze_Wilcoxon]{Analyze_Wilcoxon()}}, or \code{\link[=Analyze_Identity]{Analyze_Identity()}}
 \item \code{dfFlagged}, returned by \code{\link[=Flag]{Flag()}}
 \item \code{dfSummary}, returned by \code{\link[=Summarize]{Summarize()}}
-\item \code{dfBounds}, returned by \code{\link[=Analyze_Poisson_PredictBounds]{Analyze_Poisson_PredictBounds()}} when strMethod == 'poisson'
+\item \code{dfBounds}, returned by \code{\link[=Analyze_Poisson_PredictBounds]{Analyze_Poisson_PredictBounds()}} only when strMethod == 'poisson'
 }
 \item \code{list} \code{lCharts}, a named list with:
 \itemize{
diff --git a/man/PD_Assess.Rd b/man/PD_Assess.Rd
index 1bab2b9aa..7ea2888af 100644
--- a/man/PD_Assess.Rd
+++ b/man/PD_Assess.Rd
@@ -8,11 +8,8 @@ PD_Assess(
   dfInput,
   vThreshold = NULL,
   strMethod = "poisson",
-  strKRILabel = "PDs/Week",
+  lMapping = yaml::read_yaml(system.file("mappings", "PD_Assess.yaml", package = "gsm")),
   strGroup = "Site",
-  lTags = list(Assessment = "PD"),
-  bChart = TRUE,
-  bReturnChecks = FALSE,
   bQuiet = TRUE
 )
 }
@@ -30,39 +27,35 @@ signed-rank test (\code{strMethod} = "wilcoxon"), and \code{c(0.000895, 0.003059
 \item \code{"identity"}
 }}
 
-\item{strKRILabel}{\code{character} KRI description. Default: \code{"PDs/Week"}}
+\item{lMapping}{Column metadata with structure \code{domain$key}, where \code{key} contains the name}
 
 \item{strGroup}{\code{character} Grouping variable. \code{"Site"} (the default) uses the column named in \code{mapping$strSiteCol}. Other valid options using the default mapping are \code{"Study"} and \code{"CustomGroup"}.}
 
-\item{lTags}{\code{list} Assessment tags, a named list of tags describing the assessment that defaults
-to \code{list(Assessment = "PD")}. \code{lTags} is returned as part of the assessment (\code{lAssess$lTags})
-and each tag is added as a column in \code{lAssess$dfSummary}.}
-
-\item{bChart}{\code{logical} Generate data visualization? Default: \code{TRUE}}
-
-\item{bReturnChecks}{\code{logical} Return input checks from \code{\link[=is_mapping_valid]{is_mapping_valid()}}? Default: \code{FALSE}}
-
 \item{bQuiet}{\code{logical} Suppress warning messages? Default: \code{TRUE}}
 }
 \value{
-\code{list} Assessment, a named list with:
+\code{list} \code{lData}, a named list with:
 \itemize{
 \item each data frame in the data pipeline
 \itemize{
-\item \code{dfInput}
 \item \code{dfTransformed}, returned by \code{\link[=Transform_EventCount]{Transform_EventCount()}}
-\item \code{dfAnalyzed}, returned by \code{\link[=Analyze_Poisson]{Analyze_Poisson()}} or \code{\link[=Analyze_Wilcoxon]{Analyze_Wilcoxon()}}
+\item \code{dfAnalyzed}, returned by \code{\link[=Analyze_Poisson]{Analyze_Poisson()}}, \code{\link[=Analyze_Wilcoxon]{Analyze_Wilcoxon()}}, or \code{\link[=Analyze_Identity]{Analyze_Identity()}}
 \item \code{dfFlagged}, returned by \code{\link[=Flag]{Flag()}}
 \item \code{dfSummary}, returned by \code{\link[=Summarize]{Summarize()}}
+\item \code{dfBounds}, returned by \code{\link[=Analyze_Poisson_PredictBounds]{Analyze_Poisson_PredictBounds()}} only when strMethod == 'poisson'
 }
-\item assessment metadata
+\item \code{list} \code{lCharts}, a named list with:
 \itemize{
-\item \code{strFunctionName}
-\item \code{lTags}
+\item \code{scatter}, a ggplot2 object returned by \code{\link[=Visualize_Scatter]{Visualize_Scatter()}}
+\item \code{barMetric}, a ggplot2 object returned by \code{\link[=Visualize_Score]{Visualize_Score()}} using strType == "metric"
+\item \code{barScore}, a ggplot2 object returned by \code{\link[=Visualize_Score]{Visualize_Score()}} using strType == "score"
 }
-\item output(s)
+\item \code{list} \code{lChecks}, a named list with:
 \itemize{
-\item \code{chart}
+\item \code{dfInput}, a named list returned by \code{\link[=is_mapping_valid]{is_mapping_valid()}}
+\item \code{status}, a boolean returned by \code{\link[=is_mapping_valid]{is_mapping_valid()}}
+\item \code{mapping}, a named list that is provided as an argument to the \code{lMapping} parameter in \code{\link[=AE_Assess]{AE_Assess()}}
+\item \code{spec}, a named list used to define variable specifications
 }
 }
 }