Running ‘testthat.R’ [239s/299s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > pkg_name <- "tern"
  > library(testthat)
  > test_check(pkg_name, reporter = ParallelProgressReporter$new())
  Loading required package: tern
  Loading required package: rtables
  Loading required package: formatters
  
  Attaching package: 'formatters'
  
  The following object is masked from 'package:base':
  
      %||%
  
  Loading required package: magrittr
  
  Attaching package: 'magrittr'
  
  The following objects are masked from 'package:testthat':
  
      equals, is_less_than, not
  
  
  Attaching package: 'rtables'
  
  The following object is masked from 'package:utils':
  
      str
  
  Registered S3 method overwritten by 'tern':
    method   from 
    tidy.glm broom
  
  Attaching package: 'dplyr'
  
  The following objects are masked from 'package:stats':
  
      filter, lag
  
  The following objects are masked from 'package:base':
  
      intersect, setdiff, setequal, union
  
  ✔ | F W  S  OK | Context
  
  ⠋ [ FAIL 0 | WARN 0 | SKIP 0 | PASS 0 ] Starting up...                          
  ✔ |      7   7 | abnormal [1.5s]                                                
  
  ✔ |      5  10 | abnormal_by_baseline                                           
  
  ✔ |      3   4 | abnormal_by_marked [5.1s]                                      
  
  ✔ |      2   3 | abnormal_by_worst_grade                                        
  
  ✔ |      8  12 | abnormal_lab_worsen_by_baseline [1.7s]                         
  
  ✔ |     31  83 | analyze_variables [10.5s]                                      
  
  ✔ |      7  19 | analyze_vars_in_cols [17.4s]                                   
  
  ✔ |      2   7 | bland-altman                                                   
  
  ✔ |         16 | combination_function                                           
  
  ✔ |      9  20 | compare_variables [1.4s]                                       
  
  ✔ |      1   3 | control_logistic                                               
  
  ✔ |      1   4 | control_step                                                   
  
  ✔ |      3  11 | control_survival                                               
  
  ✔ |      8   8 | count_cumulative [1.4s]                                        
  
  ✔ |      4   4 | count_missed_doses                                             
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd A.1.1.1.1  -> { dcd A.1.1.1.1, dcd A.1.1.1.1[2], dcd A.1.1.1.1[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd A.1.1.1.2  -> { dcd A.1.1.1.2, dcd A.1.1.1.2[2], dcd A.1.1.1.2[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd B.1.1.1.1  -> { dcd B.1.1.1.1, dcd B.1.1.1.1[2], dcd B.1.1.1.1[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd B.2.1.2.1  -> { dcd B.2.1.2.1, dcd B.2.1.2.1[2], dcd B.2.1.2.1[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd B.2.2.3.1  -> { dcd B.2.2.3.1, dcd B.2.2.3.1[2], dcd B.2.2.3.1[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd C.1.1.1.3  -> { dcd C.1.1.1.3, dcd C.1.1.1.3[2], dcd C.1.1.1.3[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd C.2.1.2.1  -> { dcd C.2.1.2.1, dcd C.2.1.2.1[2], dcd C.2.1.2.1[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd D.1.1.1.1  -> { dcd D.1.1.1.1, dcd D.1.1.1.1[2], dcd D.1.1.1.1[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd D.1.1.4.2  -> { dcd D.1.1.4.2, dcd D.1.1.4.2[2], dcd D.1.1.4.2[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [dcd D.2.1.5.3  -> { dcd D.2.1.5.3, dcd D.2.1.5.3[2], dcd D.2.1.5.3[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [LOW  -> { LOW, LOW[2], LOW[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [MEDIUM  -> { MEDIUM, MEDIUM[2], MEDIUM[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [HIGH  -> { HIGH, HIGH[2], HIGH[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [LOW  -> { LOW, LOW[2], LOW[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [MEDIUM  -> { MEDIUM, MEDIUM[2], MEDIUM[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [HIGH  -> { HIGH, HIGH[2], HIGH[3] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  
  ✔ |      8  20 | count_occurrences [7.1s]                                       
  
  ✔ |     17  27 | count_occurrences_by_grade [7.1s]                              
  
  ✔ |      4   4 | count_patients_events_in_cols                                  
  
  ✔ |      8   9 | count_patients_with_event [1.7s]                               
  
  ✔ |     11  18 | count_patients_with_flags [3.0s]                               
  
  ✔ |     11  17 | count_values [2.1s]                                            
  skipping term strata(ecog.ps)
  
  ✔ |      5  15 | coxph                                                          
  
  ✔ |     24  50 | coxreg [1.8s]                                                  
  
  ✔ |      2  13 | decorate_grob [2.4s]                                           
  
  ✔ |      5   5 | desctools_binom_diff                                           
  
  ✔ |      5  13 | df_explicit_na                                                 
  
  ✔ |      3   7 | estimate_multinomial_rsp                                       
  
  ✔ |     18  24 | estimate_proportion [1.8s]                                     
  
  ✔ |      3  16 | fit_rsp_step                                                   
  
  ✔ |      3  12 | fit_survival_step                                              
  
  ✔ |     21  35 | formatting_functions [1.3s]                                    
  
  ✔ |      3  18 | g_forest [11.6s]                                               
  
  ✔ |      9  18 | g_km [18.0s]                                                   
  
  ✔ |      8  15 | g_lineplot [10.2s]                                             
  
  ✔ |      4  16 | g_step                                                         
  
  ✔ |      2   2 | g_waterfall                                                    
  
  ✔ |      5   1 | h_adsl_adlb_merge_using_worst_flag                             
  
  ✔ |      2   5 | h_biomarkers_subgroups                                         
  
  ✔ |      1   2 | h_format_row                                                   
  
  ✔ |      5   5 | h_incidence_rate                                               
  
  ✔ |     13  26 | h_km [1.7s]                                                    
  
  ✔ |     16  62 | h_logistic_regression [1.6s]                                   
  
  ✔ |      7   7 | h_map_for_count_abnormal                                       
  
  ✔ |      2   2 | h_pkparam_sort                                                 
  
  ✔ |      4   4 | h_response_biomarkers_subgroups                                
  
  ✔ |     14  15 | h_response_subgroups [1.4s]                                    
  
  ✔ |      3   8 | h_stack_by_baskets                                             
  
  ✔ |      8  62 | h_step [1.7s]                                                  
  
  ✔ |      3   6 | h_survival_biomarkers_subgroups                                
  
  ✔ |     16  20 | h_survival_duration_subgroups [1.6s]                           
  
  ✔ |      2   0 | imputation_rule                                                
  
  ✔ |      8  12 | incidence_rate [1.4s]                                          
  
  ✔ |          7 | individual_patient_plot                                        
  
  ✖ | 2    6  20 | logistic_regression [6.3s]                                     
  ────────────────────────────────────────────────────────────────────────────────
  Failure ('test-logistic_regression.R:102:3'): fit_logistic works with a single stratification variable
  Expected `result_formula` to equal `expected_formula`.
  Differences:
  actual vs expected
  - `Surv(1 + 0 * Response, Response) ~ ARMCD + RACE + AGE + strata(STRATA1)`
  + `Surv(rep(1, 20L), Response) ~ ARMCD + RACE + AGE + strata(STRATA1)`
  
  
  Failure ('test-logistic_regression.R:134:3'): fit_logistic works with two stratification variables
  Expected `result_formula` to equal `expected_formula`.
  Differences:
  actual vs expected
  - `Surv(1 + 0 * Response, Response) ~ ARMCD + RACE + AGE + strata(I(interaction(STRATA1, `
  + `Surv(rep(1, 20L), Response) ~ ARMCD + RACE + AGE + strata(I(interaction(STRATA1, `
    `    STRATA2)))`
  
  ────────────────────────────────────────────────────────────────────────────────
  
  ✔ |      7  23 | make_afun                                                      
  
  ✔ |      8  12 | odds_ratio [1.4s]                                              
  
  ✔ |     15  36 | prop_diff [1.3s]                                               
  
  ✔ |      7  33 | prune_occurrences [6.5s]                                       
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [root  -> { root, root[2] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [biomarker_label  -> { biomarker_label, biomarker_label[2] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [root  -> { root, root[2] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  
  ✔ |      6  13 | response_biomarkers_subgroups [4.9s]                           
  
  ✔ |     14  19 | response_subgroups [16.8s]                                     
  
  ✔ |      5  15 | rtables_access [7.8s]                                          
  
  ✔ |      5   8 | score_occurrences [2.2s]                                       
  
  ✔ |     15  19 | split_cols_by_groups [1.5s]                                    
  
  ✔ |      9  43 | stat                                                           
  
  ✔ |   1  5  13 | summarize_ancova [4.9s]                                        
  ────────────────────────────────────────────────────────────────────────────────
  Warning ('test-summarize_ancova.R:210:3'): summarize_ancova works with irregular arm levels
  There was 1 warning in `mutate()`.
  i In argument: `ARMCD = `%>%`(...)`.
  Caused by warning:
  ! `case_match()` was deprecated in dplyr 1.2.0.
  i Please use `recode_values()` instead.
  Backtrace:
      ▆
   1. ├─adsl %>% ... at test-summarize_ancova.R:210:3
   2. ├─dplyr::mutate(...)
   3. └─dplyr:::mutate.data.frame(...)
   4.   └─dplyr:::mutate_cols(.data, dplyr_quosures(...), by)
   5.     └─dplyr:::signal_warnings(warnings_state, error_call)
  ────────────────────────────────────────────────────────────────────────────────
  
  ✔ |      5   7 | summarize_change [1.8s]                                        
  
  ✔ |      3   3 | summarize_colvars [2.1s]                                       
  
  ✔ |     13  23 | summarize_coxreg [13.8s]                                       
  
  ✔ |     17  27 | summarize_glm_count [3.9s]                                     
  
  ✔ |     17  27 | summarize_num_patients [5.0s]                                  
  
  ✔ |      9   9 | summarize_patients_exposure_in_cols [2.0s]                     
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [root  -> { root, root[2] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [biomarker_label  -> { biomarker_label, biomarker_label[2] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [root  -> { root, root[2] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  Modifying subtable (or row) names to ensure uniqueness among direct siblings
  [root  -> { root, root[2] }]
    To control table names use split_rows_by*(, parent_name =.) or  analyze(., table_names = .) when analyzing a single variable, or analyze(., parent_name = .) when analyzing multiple variables in a single call.FALSE
  
  ✔ |      7  11 | survival_biomarkers_subgroups [7.3s]                           
  
  ✔ |      9  11 | survival_coxph_pairwise [2.4s]                                 
  
  ✔ |     14  21 | survival_duration_subgroups [17.7s]                            
  
  ✔ |      7   9 | survival_time [1.4s]                                           
  
  ✔ |     10  11 | survival_timepoint [1.7s]                                      
  
  ✔ |     16  30 | test_proportion_diff [1.8s]                                    
  
  ✔ |     59  84 | utils [2.4s]                                                   
  
  ✔ |         42 | utils_checkmate                                                
  
  ✔ |      6  47 | utils_default_stats_formats_labels                             
  
  ✔ |     13  32 | utils_factor                                                   
  
  ✔ |      3   3 | utils_ggplot [1.6s]                                            
  
  ✔ |          8 | utils_grid                                                     
  
  ✔ |     19  34 | utils_rtables [13.5s]                                          
  
  ✔ |      6  13 | utils_split_fun [4.3s]                                         
  
                                                                                  
  ══ Results ═════════════════════════════════════════════════════════════════════
  Duration: 270.3 s
  
  ── Skipped tests (709) ─────────────────────────────────────────────────────────
  • On CRAN (680): 'test-abnormal.R:1:1', 'test-abnormal.R:27:1',
    'test-abnormal.R:54:1', 'test-abnormal.R:83:1', 'test-abnormal.R:106:1',
    'test-abnormal.R:137:1', 'test-abnormal.R:163:1',
    'test-abnormal_by_baseline.R:1:1', 'test-abnormal_by_baseline.R:28:1',
    'test-abnormal_by_baseline.R:59:1', 'test-abnormal_by_baseline.R:83:1',
    'test-abnormal_by_baseline.R:97:1', 'test-abnormal_by_marked.R:28:1',
    'test-abnormal_by_marked.R:83:1', 'test-abnormal_by_marked.R:192:1',
    'test-abnormal_by_worst_grade.R:19:1', 'test-abnormal_by_worst_grade.R:46:1',
    'test-abnormal_lab_worsen_by_baseline.R:12:1',
    'test-abnormal_lab_worsen_by_baseline.R:67:1',
    'test-abnormal_lab_worsen_by_baseline.R:85:1',
    'test-abnormal_lab_worsen_by_baseline.R:105:1',
    'test-abnormal_lab_worsen_by_baseline.R:125:1',
    'test-abnormal_lab_worsen_by_baseline.R:145:1',
    'test-abnormal_lab_worsen_by_baseline.R:165:1',
    'test-abnormal_lab_worsen_by_baseline.R:187:1',
    'test-analyze_variables.R:1:1', 'test-analyze_variables.R:10:1',
    'test-analyze_variables.R:26:1', 'test-analyze_variables.R:34:1',
    'test-analyze_variables.R:42:1', 'test-analyze_variables.R:57:1',
    'test-analyze_variables.R:65:1', 'test-analyze_variables.R:75:1',
    'test-analyze_variables.R:84:1', 'test-analyze_variables.R:107:1',
    'test-analyze_variables.R:121:1', 'test-analyze_variables.R:130:1',
    'test-analyze_variables.R:137:1', 'test-analyze_variables.R:146:1',
    'test-analyze_variables.R:156:1', 'test-analyze_variables.R:221:1',
    'test-analyze_variables.R:244:1', 'test-analyze_variables.R:282:1',
    'test-analyze_variables.R:305:1', 'test-analyze_variables.R:316:1',
    'test-analyze_variables.R:331:1', 'test-analyze_variables.R:342:1',
    'test-analyze_variables.R:353:1', 'test-analyze_variables.R:373:1',
    'test-analyze_variables.R:399:1', 'test-analyze_variables.R:445:1',
    'test-analyze_variables.R:458:1', 'test-analyze_variables.R:478:1',
    'test-analyze_variables.R:495:1', 'test-analyze_variables.R:513:1',
    'test-analyze_variables.R:528:1', 'test-analyze_vars_in_cols.R:3:1',
    'test-analyze_vars_in_cols.R:42:1', 'test-analyze_vars_in_cols.R:93:1',
    'test-analyze_vars_in_cols.R:148:1', 'test-analyze_vars_in_cols.R:216:1',
    'test-analyze_vars_in_cols.R:279:1', 'test-analyze_vars_in_cols.R:384:1',
    'test-bland-altman.R:64:1', 'test-compare_variables.R:1:1',
    'test-compare_variables.R:12:1', 'test-compare_variables.R:23:1',
    'test-compare_variables.R:35:1', 'test-compare_variables.R:60:1',
    'test-compare_variables.R:72:1', 'test-compare_variables.R:93:1',
    'test-compare_variables.R:103:1', 'test-compare_variables.R:118:1',
    'test-control_logistic.R:1:1', 'test-control_step.R:1:1',
    'test-control_survival.R:1:1', 'test-control_survival.R:15:1',
    'test-control_survival.R:30:1', 'test-count_cumulative.R:1:1',
    'test-count_cumulative.R:15:1', 'test-count_cumulative.R:33:1',
    'test-count_cumulative.R:47:1', 'test-count_cumulative.R:66:1',
    'test-count_cumulative.R:85:1', 'test-count_cumulative.R:107:1',
    'test-count_cumulative.R:132:1', 'test-count_missed_doses.R:1:1',
    'test-count_missed_doses.R:8:1', 'test-count_missed_doses.R:20:1',
    'test-count_missed_doses.R:40:1', 'test-count_occurrences.R:1:1',
    'test-count_occurrences.R:57:1', 'test-count_occurrences.R:93:1',
    'test-count_occurrences.R:113:1', 'test-count_occurrences.R:139:1',
    'test-count_occurrences.R:165:1', 'test-count_occurrences.R:206:1',
    'test-count_occurrences.R:234:1', 'test-count_occurrences_by_grade.R:15:1',
    'test-count_occurrences_by_grade.R:29:1',
    'test-count_occurrences_by_grade.R:43:1',
    'test-count_occurrences_by_grade.R:60:1',
    'test-count_occurrences_by_grade.R:70:1',
    'test-count_occurrences_by_grade.R:121:1',
    'test-count_occurrences_by_grade.R:138:1',
    'test-count_occurrences_by_grade.R:150:1',
    'test-count_occurrences_by_grade.R:166:1',
    'test-count_occurrences_by_grade.R:190:1',
    'test-count_occurrences_by_grade.R:206:1',
    'test-count_occurrences_by_grade.R:246:1',
    'test-count_occurrences_by_grade.R:286:1',
    'test-count_occurrences_by_grade.R:313:1',
    'test-count_occurrences_by_grade.R:412:1',
    'test-count_occurrences_by_grade.R:446:1',
    'test-count_occurrences_by_grade.R:461:1',
    'test-count_patients_events_in_cols.R:11:1',
    'test-count_patients_events_in_cols.R:26:1',
    'test-count_patients_events_in_cols.R:42:1',
    'test-count_patients_events_in_cols.R:58:1',
    'test-count_patients_with_event.R:1:1',
    'test-count_patients_with_event.R:19:1',
    'test-count_patients_with_event.R:38:1',
    'test-count_patients_with_event.R:59:1',
    'test-count_patients_with_event.R:83:1',
    'test-count_patients_with_event.R:115:1',
    'test-count_patients_with_event.R:153:1',
    'test-count_patients_with_event.R:175:1',
    'test-count_patients_with_flags.R:1:1',
    'test-count_patients_with_flags.R:19:1',
    'test-count_patients_with_flags.R:38:1',
    'test-count_patients_with_flags.R:103:1',
    'test-count_patients_with_flags.R:128:1',
    'test-count_patients_with_flags.R:156:1',
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    'test-utils.R:440:1', 'test-utils.R:449:1', 'test-utils.R:461:1',
    'test-utils.R:473:1', 'test-utils.R:496:1', 'test-utils.R:508:1',
    'test-utils.R:520:1', 'test-utils.R:534:1', 'test-utils.R:543:1',
    'test-utils.R:555:1', 'test-utils.R:567:1', 'test-utils.R:578:1',
    'test-utils.R:587:1', 'test-utils.R:599:1', 'test-utils.R:611:1',
    'test-utils.R:625:1', 'test-utils.R:634:1', 'test-utils.R:646:1',
    'test-utils.R:658:1', 'test-utils.R:672:1', 'test-utils.R:681:1',
    'test-utils.R:693:1', 'test-utils.R:705:1',
    'test-utils_default_stats_formats_labels.R:1:1',
    'test-utils_default_stats_formats_labels.R:110:1',
    'test-utils_default_stats_formats_labels.R:204:1',
    'test-utils_default_stats_formats_labels.R:222:1',
    'test-utils_default_stats_formats_labels.R:236:1',
    'test-utils_default_stats_formats_labels.R:246:1',
    'test-utils_factor.R:17:1', 'test-utils_factor.R:28:1',
    'test-utils_factor.R:47:1', 'test-utils_factor.R:56:1',
    'test-utils_factor.R:69:1', 'test-utils_factor.R:82:1',
    'test-utils_factor.R:89:1', 'test-utils_factor.R:110:1',
    'test-utils_factor.R:133:1', 'test-utils_factor.R:143:1',
    'test-utils_factor.R:154:1', 'test-utils_factor.R:162:1',
    'test-utils_factor.R:170:1', 'test-utils_rtables.R:1:1',
    'test-utils_rtables.R:39:1', 'test-utils_rtables.R:47:1',
    'test-utils_rtables.R:55:1', 'test-utils_rtables.R:69:1',
    'test-utils_rtables.R:83:1', 'test-utils_rtables.R:90:1',
    'test-utils_rtables.R:97:1', 'test-utils_rtables.R:107:1',
    'test-utils_rtables.R:122:1', 'test-utils_rtables.R:147:1',
    'test-utils_rtables.R:162:1', 'test-utils_rtables.R:172:1',
    'test-utils_rtables.R:192:1', 'test-utils_rtables.R:205:1',
    'test-utils_rtables.R:224:1', 'test-utils_rtables.R:231:1',
    'test-utils_rtables.R:238:1', 'test-utils_rtables.R:252:1',
    'test-utils_split_fun.R:9:1', 'test-utils_split_fun.R:30:1',
    'test-utils_split_fun.R:42:1', 'test-utils_split_fun.R:59:1',
    'test-utils_split_fun.R:77:1', 'test-utils_split_fun.R:105:1'
  • no_plot_snapshots is TRUE (29): 'test-bland-altman.R:103:3',
    'test-decorate_grob.R:124:3', 'test-g_forest.R:23:3', 'test-g_forest.R:58:3',
    'test-g_forest.R:98:3', 'test-g_km.R:17:3', 'test-g_km.R:30:3',
    'test-g_km.R:42:3', 'test-g_km.R:64:3', 'test-g_km.R:79:3',
    'test-g_km.R:116:3', 'test-g_km.R:130:3', 'test-g_km.R:149:3',
    'test-g_km.R:164:3', 'test-g_lineplot.R:9:3', 'test-g_lineplot.R:32:3',
    'test-g_lineplot.R:52:3', 'test-g_lineplot.R:70:3',
    'test-g_lineplot.R:101:3', 'test-g_lineplot.R:114:3',
    'test-g_lineplot.R:249:3', 'test-g_lineplot.R:273:3', 'test-g_step.R:18:3',
    'test-g_step.R:28:3', 'test-g_waterfall.R:7:3', 'test-g_waterfall.R:29:3',
    'test-utils_ggplot.R:19:3', 'test-utils_ggplot.R:53:3',
    'test-utils_ggplot.R:59:3'
  
  ── Failed tests ────────────────────────────────────────────────────────────────
  Failure ('test-logistic_regression.R:102:3'): fit_logistic works with a single stratification variable
  Expected `result_formula` to equal `expected_formula`.
  Differences:
  actual vs expected
  - `Surv(1 + 0 * Response, Response) ~ ARMCD + RACE + AGE + strata(STRATA1)`
  + `Surv(rep(1, 20L), Response) ~ ARMCD + RACE + AGE + strata(STRATA1)`
  
  
  Failure ('test-logistic_regression.R:134:3'): fit_logistic works with two stratification variables
  Expected `result_formula` to equal `expected_formula`.
  Differences:
  actual vs expected
  - `Surv(1 + 0 * Response, Response) ~ ARMCD + RACE + AGE + strata(I(interaction(STRATA1, `
  + `Surv(rep(1, 20L), Response) ~ ARMCD + RACE + AGE + strata(I(interaction(STRATA1, `
    `    STRATA2)))`
  
  
  [ FAIL 2 | WARN 1 | SKIP 709 | PASS 1515 ]
  Deleting unused snapshots: 'g_forest/g_forest_custom_2.svg',
  'g_forest/g_forest_custom_3.svg', 'g_forest/g_forest_or.svg',
  'g_forest/g_forest_plot_only.svg', 'g_km/g_km_crop_ylim_failure.svg',
  'g_km/g_km_custom_ylim.svg', 'g_km/g_km_table_only.svg',
  'g_lineplot/g_lineplot_table_only.svg', 'g_lineplot/g_lineplot_xlim_ylim.svg',
  'g_lineplot/g_lineplot_xticks.svg', 'utils_ggplot/df2gg_cw.svg',
  'utils_ggplot/df2gg_fs.svg', 'utils_ggplot/rtable2gg_cw.svg',
  'utils_ggplot/rtable2gg_fs.svg', and 'utils_ggplot/rtable2gg_lblpad.svg'
  Error:
  ! Test failures.
  Execution halted