Merge pull request #280 from OHDSI/issue_188

renaming of estimates
OHDSI · Dec 20, 2024 · 7a24da8 · 7a24da8
2 parents c297a86 + 5ad600f
commit 7a24da8
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Showing 11 changed files with 88 additions and 82 deletions.
diff --git a/R/plotObservationPeriod.R b/R/plotObservationPeriod.R
@@ -20,14 +20,14 @@
 #'
 #' result |>
 #'   plotObservationPeriod(
-#'     variableName = "duration in days",
+#'     variableName = "Duration in days",
 #'     plotType = "boxplot"
 #'   )
 #'
 #' PatientProfiles::mockDisconnect(cdm)
 #' }
 plotObservationPeriod <- function(result,
-                                  variableName = "number subjects",
+                                  variableName = "Number subjects",
                                   plotType = "barplot",
                                   facet = NULL,
                                   colour = NULL) {
@@ -110,13 +110,13 @@ plotObservationPeriod <- function(result,
 availablePlotObservationPeriod <- function() {
   dplyr::tribble(
     ~variable_name, ~plot_type, ~facet,
-    "number subjects", "barplot", "cdm_name+observation_period_ordinal",
-    "records per person", "densityplot", "cdm_name",
-    "records per person", "boxplot", "cdm_name",
-    "duration in days", "densityplot", "cdm_name+observation_period_ordinal",
-    "duration in days", "boxplot", "cdm_name+observation_period_ordinal",
-    "days to next observation period", "densityplot", "cdm_name+observation_period_ordinal",
-    "days to next observation period", "boxplot", "cdm_name+observation_period_ordinal",
+    "Number subjects", "barplot", "cdm_name+observation_period_ordinal",
+    "Records per person", "densityplot", "cdm_name",
+    "Records per person", "boxplot", "cdm_name",
+    "Duration in days", "densityplot", "cdm_name+observation_period_ordinal",
+    "Duration in days", "boxplot", "cdm_name+observation_period_ordinal",
+    "Days to next observation period", "densityplot", "cdm_name+observation_period_ordinal",
+    "Days to next observation period", "boxplot", "cdm_name+observation_period_ordinal",
   )
 }
 needEstimates <- function(plotType) {

diff --git a/R/summariseAllConceptCounts.R b/R/summariseAllConceptCounts.R
@@ -101,7 +101,10 @@ summariseAllConceptCounts <- function(cdm,
       ) |>
       # summarise results
       summariseCountsInternal(stratax, counts) |>
-      dplyr::mutate(omop_table = .env$table)
+      dplyr::mutate(omop_table = .env$table,
+                    estimate_name = dplyr::if_else(.data$estimate_name == "count_records", "Number records",
+                                                   dplyr::if_else(.data$estimate_name == "count_subjects", "Number subjects", .data$estimate_name)
+                    ))
 
     omopgenerics::dropSourceTable(cdm = cdm, name = dplyr::starts_with(prefix))
 

diff --git a/R/summariseClinicalRecords.R b/R/summariseClinicalRecords.R
@@ -163,7 +163,7 @@ summariseClinicalRecords <- function(cdm,
     # Summary
     if (inObservation | standardConcept | sourceVocabulary | domainId | typeConcept) {
       denominator <- resultsRecordPerPerson |>
-        dplyr::filter(.data$variable_name == "number records") |>
+        dplyr::filter(.data$variable_name == "Number records") |>
         dplyr::select("strata_name", "strata_level", den = "estimate_value")
       variables <- variablesToSummarise(
         inObservation, standardConcept, sourceVocabulary, domainId, typeConcept
@@ -258,7 +258,7 @@ summariseClinicalRecords <- function(cdm,
       dplyr::select("strata_name", "strata_level") |>
       dplyr::distinct() |>
       dplyr::cross_join(dplyr::tibble(variable_name = unique(c(
-        "number subjects", "number records", "records_per_person",
+        "Number subjects", "Number records", "records_per_person",
         unique(fullResult$variable_name)
       )))) |>
       dplyr::mutate(order_id = dplyr::row_number()) |>
@@ -319,17 +319,18 @@ summariseRecordsPerPerson <- function(x, den, strata, estimates) {
         variables = list("number_subjects", "n"),
         estimates = list(c("count", "percentage"), c(estimates, "sum"))
       ) |>
-      suppressMessages()
-  }) |>
+      suppressMessages() |>
+      dplyr::mutate(variable_name = dplyr::if_else(.data$variable_name == "number subjects", "Number subjects", .data$variable_name))
+}) |>
     dplyr::bind_rows() |>
     dplyr::mutate(
       variable_name = dplyr::if_else(
         .data$variable_name == "n",
-        dplyr::if_else(.data$estimate_name == "sum", "number records", "records_per_person"),
+        dplyr::if_else(.data$estimate_name == "sum", "Number records", "records_per_person"),
         .data$variable_name
       ),
       estimate_name = dplyr::if_else(
-        .data$variable_name == "number records", "count", .data$estimate_name
+        .data$variable_name == "Number records", "count", .data$estimate_name
       ),
       estimate_value = reduceDemicals(.data$estimate_value, 4)
     )

diff --git a/R/summariseInternal.R b/R/summariseInternal.R
@@ -5,7 +5,7 @@ summariseCountsInternal <- function(x, strata, counts) {
     'dplyr::n_distinct(.data$person_id)',
     'dplyr::n_distinct(.data$subject_id)'
   ) |>
-    rlang::set_names(c("count_records", "count_subjecst", "count_subjects")) |>
+    rlang::set_names(c("count_records", "count_subjects", "count_subjects")) |>
     purrr::keep(c("records", "person_id", "subject_id") %in% counts) |>
     rlang::parse_exprs()
   purrr::map(strata, \(stratak) {

diff --git a/R/summariseObservationPeriod.R b/R/summariseObservationPeriod.R
@@ -93,6 +93,8 @@ summariseObservationPeriod <- function(observationPeriod,
         estimates = estimates
       ) |>
       suppressMessages() |>
+      dplyr::mutate(variable_name = dplyr::if_else(.data$variable_name == "number records", "Number records",
+                                                   dplyr::if_else(.data$variable_name == "number subjects", "Number subjects" , .data$variable_name))) |>
         dplyr::union_all(
           obs |>
             dplyr::group_by(.data$person_id, dplyr::across(dplyr::any_of(c("sex","age_group")))) |>
@@ -107,17 +109,17 @@ summariseObservationPeriod <- function(observationPeriod,
             suppressMessages()
           ) |>
       addOrdinalLevels() |>
-      dplyr::filter(.data$variable_name != "number records" | .data$group_level == "all") |>
+      dplyr::filter(.data$variable_name != "Number records" | .data$group_level == "all") |>
       arrangeSr(estimates)
   }
 
   obsSr <- obsSr |>
     dplyr::mutate(
       "cdm_name" = omopgenerics::cdmName(cdm),
       "variable_name" = dplyr::case_when(
-        .data$variable_name == "n" ~ "records per person",
-        .data$variable_name == "next_obs" ~ "days to next observation period",
-        .data$variable_name == "duration" ~ "duration in days",
+        .data$variable_name == "n" ~ "Records per person",
+        .data$variable_name == "next_obs" ~ "Days to next observation period",
+        .data$variable_name == "duration" ~ "Duration in days",
         .default = .data$variable_name
       )
     ) |>
@@ -158,14 +160,14 @@ arrangeSr <- function(x, estimates) {
   group <- c("all", sort(group[group != "all"]))
 
   order <- dplyr::tibble(
-    "variable_name" = c("number records"),
+    "variable_name" = c("Number records"),
     "group_level"   = "all",
     "strata_level"  = lev,
     "estimate_name" = "count"
   ) |>
     dplyr::union_all(
       tidyr::expand_grid(
-        "variable_name" = c("number subjects"),
+        "variable_name" = c("Number subjects"),
         "group_level"   = group,
         "strata_level"  = lev,
         "estimate_name" = "count"
@@ -191,7 +193,7 @@ arrangeSr <- function(x, estimates) {
     ) |>
     dplyr::left_join(
       dplyr::tibble("variable_name" = c(
-        "number records", "number subjects", "n", "duration", "next_obs"
+        "Number records", "Number subjects", "n", "duration", "next_obs"
       )) |>
         dplyr::mutate("order_var" = dplyr::row_number()),
       by = "variable_name"

diff --git a/R/summariseRecordCount.R b/R/summariseRecordCount.R
@@ -112,7 +112,7 @@ summariseRecordCount <- function(cdm,
       dplyr::mutate(
         omop_table = .env$table,
         estimate_name = "count",
-        variable_name = "incident_counts",
+        variable_name = "Number records",
         variable_level = getVariableLevel(.data$additional_level),
         result_id = 1L,
         cdm_name = omopgenerics::cdmName(cdm)

diff --git a/README.Rmd b/README.Rmd
@@ -97,7 +97,7 @@ OmopSketch also provides functions to explore some of (or all) the concepts in t
 acetaminophen <- c(1125315,  1127433, 1127078)
 
 summariseConceptSetCounts(cdm, conceptSet = list("acetaminophen" = acetaminophen)) |>
-  filter(estimate_name == "record_count") |> 
+  filter(variable_name == "Number records") |> 
   plotConceptSetCounts()
 ```
 

diff --git a/man/plotObservationPeriod.Rd b/man/plotObservationPeriod.Rd
diff --git a/tests/testthat/test-summariseClinicalRecords.R b/tests/testthat/test-summariseClinicalRecords.R
@@ -138,12 +138,12 @@ test_that("summariseClinicalRecords() sex and ageGroup argument work", {
     dplyr::mutate(dplyr::across(dplyr::everything(), as.character))
 
   m_records  <- m |>
-    dplyr::filter(variable_name == "number records", strata_level %in% c("<30", ">= 30"), estimate_name == "count") |>
+    dplyr::filter(variable_name == "Number records", strata_level %in% c("<30", ">= 30"), estimate_name == "count") |>
     dplyr::select("age_group" = "strata_level", "estimate_value") |>
     dplyr::collect() |>
     dplyr::arrange(age_group)
   m_subjects <- m |>
-    dplyr::filter(variable_name == "number subjects", strata_level %in% c("<30", ">= 30"), estimate_name == "count") |>
+    dplyr::filter(variable_name == "Number subjects", strata_level %in% c("<30", ">= 30"), estimate_name == "count") |>
     dplyr::select("age_group" = "strata_level", "estimate_value") |>
     dplyr::collect() |>
     dplyr::arrange(age_group)
@@ -153,7 +153,7 @@ test_that("summariseClinicalRecords() sex and ageGroup argument work", {
 
   # Check sex and age group---
   x <- summariseClinicalRecords(cdm, "condition_occurrence", sex = TRUE, ageGroup = list(">= 30" = c(30, Inf), "<30" = c(0, 29))) |>
-    dplyr::filter(variable_name == "number subjects", estimate_name == "count",
+    dplyr::filter(variable_name == "Number subjects", estimate_name == "count",
                   strata_name == "sex" | strata_name == "overall") |>
     dplyr::select("strata_name", "strata_level", "estimate_value") |>
     dplyr::mutate(group = dplyr::if_else(strata_name == "overall",1, 2)) |>
@@ -162,7 +162,7 @@ test_that("summariseClinicalRecords() sex and ageGroup argument work", {
   expect_equal(x$n[[1]], x$n[[2]])
 
   x <- summariseClinicalRecords(cdm, "condition_occurrence", sex = TRUE, ageGroup = list(">= 30" = c(30, Inf), "<30" = c(0, 29))) |>
-    dplyr::filter(variable_name == "number records", estimate_name == "count",
+    dplyr::filter(variable_name == "Number records", estimate_name == "count",
                   strata_name == "sex" | strata_name == "overall") |>
     dplyr::select("strata_name", "strata_level", "estimate_value") |>
     dplyr::mutate(group = dplyr::if_else(strata_name == "overall",1, 2)) |>
@@ -171,7 +171,7 @@ test_that("summariseClinicalRecords() sex and ageGroup argument work", {
   expect_equal(x$n[[1]], x$n[[2]])
 
   x <- summariseClinicalRecords(cdm, "condition_occurrence", sex = TRUE, ageGroup = list(">= 30" = c(30, Inf), "<30" = c(0, 29))) |>
-    dplyr::filter(variable_name == "number records", estimate_name == "count",
+    dplyr::filter(variable_name == "Number records", estimate_name == "count",
                   strata_name == "age_group" | strata_name == "overall") |>
     dplyr::select("strata_name", "strata_level", "estimate_value") |>
     dplyr::mutate(group = dplyr::if_else(strata_name == "overall",1, 2)) |>
@@ -229,7 +229,7 @@ test_that("summariseClinicalRecords() sex and ageGroup argument work", {
 
   # Check num records
   records <- result |>
-    dplyr::filter(variable_name == "number records", estimate_name == "count")
+    dplyr::filter(variable_name == "Number records", estimate_name == "count")
   expect_identical(records |> dplyr::filter(strata_name == "overall") |> dplyr::pull(estimate_value), "9")
   expect_identical(records |> dplyr::filter(strata_level == "old") |> dplyr::pull(estimate_value), "5")
   expect_identical(records |> dplyr::filter(strata_level == "young") |> dplyr::pull(estimate_value), "4")

diff --git a/tests/testthat/test-summariseConceptSetCounts.R b/tests/testthat/test-summariseConceptSetCounts.R
@@ -578,17 +578,17 @@ test_that("interval argument works", {
   skip_on_cran()
   # Load mock database ----
   cdm <- mockOmopSketch()
-  expect_no_error(y<-summariseConceptCounts(list(ANTIHISTAMINES= c(21603444)),
+  expect_no_error(y<-summariseConceptSetCounts(list(ANTIHISTAMINES= c(21603444)),
                          cdm = cdm,
                          interval = "years"))
 
-  expect_no_error(o<-summariseConceptCounts(list(ANTIHISTAMINES= c(21603444)),
+  expect_no_error(o<-summariseConceptSetCounts(list(ANTIHISTAMINES= c(21603444)),
                                             cdm = cdm,
                                             interval = "overall"))
-  expect_no_error(q<-summariseConceptCounts(list(ANTIHISTAMINES= c(21603444)),
+  expect_no_error(q<-summariseConceptSetCounts(list(ANTIHISTAMINES= c(21603444)),
                                             cdm = cdm,
                                             interval = "quarters"))
-  expect_no_error(m<-summariseConceptCounts(list(ANTIHISTAMINES= c(21603444)),
+  expect_no_error(m<-summariseConceptSetCounts(list(ANTIHISTAMINES= c(21603444)),
                                             cdm = cdm,
                                             interval = "months"))