Merge pull request #225 from OHDSI/dev_cc

creates tables for summariseMissingData and summariseAllConceptCount

NAMESPACE

@@ -9,14 +9,18 @@ export(plotInObservation)
 export(plotObservationPeriod)
 export(plotRecordCount)
 export(settings)
+export(summariseAllConceptCounts)
 export(summariseClinicalRecords)
 export(summariseConceptCounts)
 export(summariseInObservation)
+export(summariseMissingData)
 export(summariseObservationPeriod)
 export(summariseOmopSnapshot)
 export(summariseRecordCount)
 export(suppress)
+export(tableAllConceptCounts)
 export(tableClinicalRecords)
+export(tableMissingData)
 export(tableObservationPeriod)
 export(tableOmopSnapshot)
 importFrom(dplyr,"%>%")

R/summariseAllConceptCounts.R

@@ -16,6 +16,7 @@ my_getStrataList <- function(sex = FALSE, ageGroup = NULL, year = FALSE){
   return(strata)
 }
 
+
 checkFeasibility <- function(omopTable, tableName, conceptId){
 
   if (omopgenerics::isTableEmpty(omopTable)){
@@ -37,6 +38,7 @@ checkFeasibility <- function(omopTable, tableName, conceptId){
   }
   return(TRUE)
 }
+
 #' Summarise concept use in patient-level data
 #'
 #' @param cdm A cdm object
@@ -74,6 +76,7 @@ summariseAllConceptCounts <- function(cdm,
 
 
 
+
   omopTable <- cdm[[table]] |>
     dplyr::ungroup()
 
@@ -143,6 +146,7 @@ summariseAllConceptCounts <- function(cdm,
   result<- result |>
     dplyr::mutate("omop_table" = table,
                   "variable_level" = as.character(.data[[conceptId]])) |>
+
     dplyr::select(-dplyr::all_of(conceptId))
     return(result)
   })

R/summariseMissingData.R

@@ -6,12 +6,12 @@
 #' @param col A character vector of column names to check for missing values.
 #' If `NULL`, all columns in the specified tables are checked. Default is `NULL`.
 #' @param sex TRUE or FALSE. If TRUE code use will be summarised by sex.
+#' @param year TRUE or FALSE. If TRUE code use will be summarised by year.
 #' @param ageGroup A list of ageGroup vectors of length two. Code use will be
 #' thus summarised by age groups.
 #' @return A summarised_result object with results overall and, if specified, by
 #' strata.
 #' @export
-
 summariseMissingData <- function(cdm,
                                  omopTableName,
                                  col = NULL,
@@ -66,8 +66,8 @@ summariseMissingData <- function(cdm,
         stratified_result |>
           dplyr::group_by(dplyr::across(dplyr::all_of(g))) |>
           dplyr::summarise(
-            na_count = sum(na_count, na.rm = TRUE),
-            total_count = sum(total_count, na.rm = TRUE),
+            na_count = sum(.data$na_count, na.rm = TRUE),
+            total_count = sum(.data$total_count, na.rm = TRUE),
             colName = c,
             .groups = "drop"
           ) |>
@@ -94,11 +94,11 @@ summariseMissingData <- function(cdm,
     purrr::reduce(dplyr::union)|>
     dplyr::mutate(dplyr::across(dplyr::all_of(strata), ~ dplyr::coalesce(., "overall")))|>
     dplyr::mutate(
-      na_count = as.double(na_count),     # Cast na_count to double
-      na_percentage = as.double(na_percentage)
+      na_count = as.double(.data$na_count),     # Cast na_count to double
+      na_percentage = as.double(.data$na_percentage)
     )|>
     tidyr::pivot_longer(
-      cols = c(na_count, na_percentage),
+      cols = c(.data$na_count, .data$na_percentage),
       names_to = "estimate_name",
       values_to = "estimate_value"
     )
@@ -118,7 +118,7 @@ summariseMissingData <- function(cdm,
       "variable_level" = NA_character_
     ) |>
     dplyr::rename("variable_name" = "colName") |>
-    dplyr::select(!c(total_count))
+    dplyr::select(!c(.data$total_count))
 
   settings <- dplyr::tibble(
     result_id = unique(sr$result_id),

R/tableAllConceptCounts.R

@@ -0,0 +1,45 @@
+#' Create a visual table from a summariseAllConceptCounts() result.
+#' @param result A summarised_result object.
+#' @param type Type of formatting output table, either "gt" or "flextable".
+#' @return A gt or flextable object with the summarised data.
+#' @export
+#'
+#'
+tableAllConceptCounts <- function(result,
+                             type = "gt") {
+  # initial checks
+  omopgenerics::validateResultArgument(result)
+  omopgenerics::assertChoice(type, choicesTables())
+
+  # subset to result_type of interest
+  result <- result |>
+    visOmopResults::filterSettings(
+      .data$result_type == "summarise_all_concept_counts")
+
+  # check if it is empty
+  if (nrow(result) == 0) {
+    warnEmpty("summarise_all_concept_counts")
+    return(emptyTable(type))
+  }
+
+  estimate_names <- result |>
+    dplyr::distinct(.data$estimate_name) |>
+    dplyr::pull()
+  estimateName <- c()
+  if ("record_count" %in% estimate_names) {
+    estimateName <- c(estimateName, "N records" = "<record_count>")
+  }
+  if ("person_count" %in% estimate_names) {
+    estimateName <- c(estimateName, "N persons" = "<person_count>")
+  }
+
+  result |>
+    formatColumn(c("variable_name", "variable_level")) |>
+    visOmopResults::visOmopTable(
+      type = type,
+      estimateName = estimateName,
+        header = c("cdm_name"),
+        rename = c("Database name" = "cdm_name"),
+        groupColumn = c("omop_table", visOmopResults::strataColumns(result))
+      )
+}

R/tableMissingData.R

@@ -0,0 +1,36 @@
+#' Create a visual table from a summariseMissingData() result.
+#' @param result A summarised_result object.
+#' @param type Type of formatting output table, either "gt" or "flextable".
+#' @return A gt or flextable object with the summarised data.
+#' @export
+#'
+#'
+tableMissingData <- function(result,
+                                 type = "gt") {
+  # initial checks
+  omopgenerics::validateResultArgument(result)
+  omopgenerics::assertChoice(type, choicesTables())
+
+  # subset to result_type of interest
+  result <- result |>
+    visOmopResults::filterSettings(
+      .data$result_type == "summarise_missing_data")
+
+  # check if it is empty
+  if (nrow(result) == 0) {
+    warnEmpty("summarise_missing_data")
+    return(emptyTable(type))
+  }
+
+  result |>
+    formatColumn(c("variable_name", "variable_level")) |>
+    visOmopResults::visOmopTable(
+      type = type,
+      estimateName = c(
+        "N (%)" = "<na_percentage> (%)",
+        "N" = "<na_count>"),
+      header = c("cdm_name"),
+      rename = c("Database name" = "cdm_name"),
+      groupColumn = c("omop_table", visOmopResults::strataColumns(result))
+    )
+}

_pkgdown.yml

@@ -15,6 +15,8 @@ reference:
   - tableClinicalRecords
   - summariseRecordCount
   - plotRecordCount
+  - summariseMissingData
+  - tableMissingData
 - subtitle: Observation Periods
   desc: Summarise and plot the observation period table in the OMOP Common Data Model
 - contents:
@@ -28,6 +30,8 @@ reference:
 - contents:
   - summariseConceptCounts
   - plotConceptCounts
+  - summariseAllConceptCounts
+  - tableAllConceptCounts
 - subtitle: Mock Database
   desc: Create a mock database to test the OmopSketch package
 - contents:

tests/testthat/test-summariseMissingData.R

@@ -9,10 +9,12 @@ test_that("summariseMissingData() works", {
   expect_no_error(x<-summariseMissingData(cdm, "visit_occurrence"))
   expect_no_error(summariseMissingData(cdm, "condition_occurrence"))
   expect_no_error(summariseMissingData(cdm, "drug_exposure"))
+
   expect_no_error(summariseMissingData(cdm, "procedure_occurrence", year = TRUE))
   expect_warning(summariseMissingData(cdm, "device_exposure"))
   expect_no_error(z<-summariseMissingData(cdm, "measurement"))
   expect_no_error(s<-summariseMissingData(cdm, "observation"))
+
   expect_warning(summariseMissingData(cdm, "death"))