test(JnJ): ✅ Added table_jnj_tbl1 (#196)

Added a test to check that a factor variable with all values missing
would produce a correct table using tern::analyze_vars

---------

Signed-off-by: Joe Zhu <[email protected]>
Co-authored-by: Joe Zhu <[email protected]>
Co-authored-by: github-actions <41898282+github-actions[bot]@users.noreply.github.com>

Author: 3 people

DESCRIPTION

@@ -25,7 +25,7 @@ Depends:
     R (>= 4.2),
     rlistings (>= 0.2.10),
     rtables (>= 0.6.11.9017),
-    tern (>= 0.9.7.9018)
+    tern (>= 0.9.9.9003)
 Imports:
     pharmaverseadam (>= 1.1.0.9001),
     random.cdisc.data (>= 0.3.16)
@@ -56,4 +56,4 @@ Encoding: UTF-8
 Language: en-US
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.2
+RoxygenNote: 7.3.3

man/scda.test-package.Rd

@@ -0,0 +1,21 @@
+# DMT01 variant factor with only Missing values
+
+    Code
+      res
+    Output
+                                 Placebo     Screen Failure   Xanomeline High Dose   Xanomeline Low Dose
+                                 (N=86)          (N=52)              (N=72)                (N=96)       
+      ——————————————————————————————————————————————————————————————————————————————————————————————————
+      Age (yr)                                                                                          
+        n                          86              52                  72                    96         
+        Mean (SD)              75.2 (8.6)      75.1 (9.7)          73.8 (7.9)            76.0 (8.1)     
+        Median                    76.0            76.0                75.5                  78.0        
+        Min - Max              52.0 - 89.0    50.0 - 89.0         56.0 - 88.0            51.0 - 88.0    
+      Age Group                                                                                         
+        n                          86              52                  72                    96         
+        18-40                       0              0                   0                      0         
+        41-64                  14 (16.3%)      9 (17.3%)           11 (15.3%)             8 (8.3%)      
+        >=65                   72 (83.7%)      43 (82.7%)          61 (84.7%)            88 (91.7%)     
+      Biomarker 1 Categories                                                                            
+        n                           0              0                   0                      0         
+

tests/testthat/_snaps/table_jnj_tbl1.md

@@ -0,0 +1,56 @@
+# extra special case situation to scenario from test-table_dmt01.R
+# Tests DMT01 with corner case situation to demonstrate bug in analyze is resolved with empty factor data
+# tern@1431-bug-s_summaryfactor
+set.seed(1)
+
+adsl <- pharmaverseadam::adsl
+adsl <- adsl %>%
+  mutate(BMRKR1 = rnorm(nrow(adsl), 3.5, 10)) %>%
+  mutate(STRATA1 = factor(sample(c("A", "B", "C"), nrow(adsl), TRUE)))
+
+adsl <- df_explicit_na(adsl)
+
+adsl <- adsl %>%
+  mutate(
+    SEX = factor(case_when(
+      SEX == "M" ~ "Male",
+      SEX == "F" ~ "Female",
+      SEX == "U" ~ "Unknown",
+      SEX == "UNDIFFERENTIATED" ~ "Undifferentiated"
+    )),
+    AGEGR1 = factor(
+      case_when(
+        between(AGE, 18, 40) ~ "18-40",
+        between(AGE, 41, 64) ~ "41-64",
+        AGE > 64 ~ ">=65"
+      ),
+      levels = c("18-40", "41-64", ">=65")
+    ),
+    BMRKR1_CAT = NA_character_
+  ) %>%
+  var_relabel(
+    BMRKR1_CAT = "Biomarker 1 Categories"
+  )
+
+adsl <- df_explicit_na(adsl, na_level = "<Missing>")
+
+
+testthat::test_that("DMT01 variant factor with only Missing values", {
+  vars <- c("AGE", "AGEGR1", "BMRKR1_CAT")
+  var_labels <- c(
+    "Age (yr)",
+    "Age Group",
+    "Biomarker 1 Categories"
+  )
+
+  result <- basic_table(show_colcounts = TRUE) %>%
+    split_cols_by(var = "ACTARM") %>%
+    analyze_vars(
+      vars = vars,
+      var_labels = var_labels
+    ) %>%
+    build_table(adsl)
+
+  res <- testthat::expect_silent(result)
+  testthat::expect_snapshot(res)
+})