Merge pull request #91 from openpharma/dev

#86

Author: erblast

R/simaerep_plot.R

@@ -500,7 +500,8 @@ plot_study <- function(df_visit,
         "study_id",
         "site_number",
         "alert_level_site",
-        "alert_level_study")))
+        "alert_level_study")),
+        by = c("study_id", "site_number"))
   }
 
 

README.Rmd

@@ -60,7 +60,7 @@ Koneswarakantha, B., Adyanthaya, R., Emerson, J. et al. An Open-Source R Package
 
 Koneswarakantha, B., Barmaz, Y., Ménard, T. et al. Follow-up on the Use of Advanced Analytics for Clinical Quality Assurance: Bootstrap Resampling to Enhance Detection of Adverse Event Under-Reporting. Drug Saf (2020). [https://doi.org/10.1007/s40264-020-01011-5](https://doi.org/10.1007/s40264-020-01011-5)
 
-## Ressources
+## Resources
 
 - [Slides PHUSE conference](https://phuse.s3.eu-central-1.amazonaws.com/Archive/2024/Connect/EU/Strasbourg/PRE_AR04.pdf)
 - [Article PHUSE conference](https://phuse.s3.eu-central-1.amazonaws.com/Archive/2024/Connect/EU/Strasbourg/PAP_AR04.pdf)

README.md

@@ -72,7 +72,7 @@ of Advanced Analytics for Clinical Quality Assurance: Bootstrap
 Resampling to Enhance Detection of Adverse Event Under-Reporting. Drug
 Saf (2020). <https://doi.org/10.1007/s40264-020-01011-5>
 
-## Ressources
+## Resources
 
 - [Slides PHUSE
   conference](https://phuse.s3.eu-central-1.amazonaws.com/Archive/2024/Connect/EU/Strasbourg/PRE_AR04.pdf)

cran-comments.md

@@ -1,5 +1,9 @@
 # submission simaerep v0.7.0
 
+## Resubmission
+
+- long running tests using duckdb are now skipped_on_cran
+
 ## Test Results
 
 No notes, warnings or errors

inst/WORDLIST

@@ -18,6 +18,7 @@ Innov
 Lifecycle
 Modelling
 Ménard
+PHUSE
 RBQM
 Regul
 Saf
@@ -78,7 +79,7 @@ purrr
 pval
 pvalue
 quALity
-reporducibly
+reproducibly
 rmarkdown
 rnorm
 rpois

man/figures/README-unnamed-chunk-4-1.png

@@ -36,7 +36,8 @@ test_that("sim_test_data_study() produces the expected output for n_ae, regardle
   ae_rates_test_sd <- sim_test_data_events %>%
     filter(visit %in% c(1, 2)) %>%
     group_by(site_number, patnum) %>%
-    summarise(stdev = sd(n_ae))
+    summarise(stdev = sd(n_ae), .groups = "drop")
+
   expect_true(unique(ae_rates_test_sd[["stdev"]]) == 0
               & length(unique(ae_rates_test_sd[["stdev"]])) == 1)
 
@@ -178,14 +179,19 @@ test_that("plot.simaerep works with event_names", {
   expect_s3_class(plot(aerep, what = "ur", study = "A", plot_event = "y"), "ggplot")
   expect_s3_class(plot(aerep, what = "ur", study = "A", plot_event = events), "ggplot")
 
-  expect_s3_class(plot(aerep, what = "med75", study = "A", plot_event = events), "ggplot")
+  expect_s3_class(
+    plot(aerep, what = "med75", study = "A", plot_event = events, verbose = FALSE),
+    "ggplot"
+  )
 
 })
 
 
 
 test_that("event_names works with duckdb backend", {
 
+  skip_on_cran()
+
   events <- c("x", "y")
 
   suffix <- c(

tests/testthat/test_event_names.R

@@ -115,6 +115,8 @@ test_that("simaerep_inframe and simaerep_visit_med75 must have similar results",
 
 test_that("simaerep_inframe must have identical counts and flags with duckdb backend", {
 
+  skip_on_cran()
+
   df_eval_med75 <- simaerep(df_visit_test, inframe = TRUE, visit_med75 = TRUE)$df_eval
   df_eval <- simaerep(df_visit_test, inframe = TRUE, visit_med75 = FALSE)$df_eval
 
@@ -195,6 +197,9 @@ test_that("p.adjust result near p_adjust_bh_inframe", {
 })
 
 test_that("p.adjust result near p_adjust_bh_inframe with duckdb", {
+
+  skip_on_cran()
+
   x <- rnorm(50, mean = c(rep(0, 500), rep(3, 500)))
   p <- 2 * pnorm(sort(-abs(x)))