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alphabetical order of staged.deps + biomarker-catalog #895

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merged 3 commits into from
May 3, 2023

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Melkiades
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Fixes #890

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@shajoezhu shajoezhu left a comment

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thanks @Melkiades , can you also add https://github.com/insightsengineering/tlg-catalog in the downstram

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github-actions bot commented May 2, 2023

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Code Coverage Summary

Filename                                   Stmts    Miss  Cover    Missing
---------------------------------------  -------  ------  -------  ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
R/abnormal_by_baseline.R                      63       0  100.00%
R/abnormal_by_marked.R                        52       5  90.38%   126-130
R/abnormal_by_worst_grade_worsen.R           113       3  97.35%   230-232
R/abnormal_by_worst_grade.R                   37       0  100.00%
R/abnormal.R                                  40       0  100.00%
R/analyze_vars_in_cols.R                      37       1  97.30%   114
R/combination_function.R                       9       0  100.00%
R/compare_variables.R                        138       3  97.83%   132, 242, 259
R/control_incidence_rate.R                    10       0  100.00%
R/control_logistic.R                           7       0  100.00%
R/control_step.R                              23       1  95.65%   58
R/control_survival.R                          15       0  100.00%
R/count_cumulative.R                          47       1  97.87%   61
R/count_missed_doses.R                        31       0  100.00%
R/count_occurrences_by_grade.R                84       6  92.86%   152-154, 157, 172-173
R/count_occurrences.R                         61       1  98.36%   90
R/count_patients_events_in_cols.R             67       1  98.51%   73
R/count_patients_with_event.R                 72       0  100.00%
R/count_values.R                              24       0  100.00%
R/cox_regression_inter.R                     142       0  100.00%
R/cox_regression.R                           161       0  100.00%
R/coxph.R                                    168       7  95.83%   224-228, 272, 287, 295, 301-302
R/d_pkparam.R                                406       0  100.00%
R/decorate_grob.R                            167       6  96.41%   269-275, 382, 414, 424, 431
R/desctools_binom_diff.R                     663      66  90.05%   66, 101-102, 142-143, 146, 225, 251-260, 299, 301, 321, 325, 329, 333, 390, 393, 396, 399, 460, 468, 480-481, 487-490, 498, 501, 510, 513, 561-562, 564-565, 567-568, 570-571, 641, 653-666, 671, 718, 731, 735
R/df_explicit_na.R                            30       0  100.00%
R/estimate_multinomial_rsp.R                  47       1  97.87%   56
R/estimate_proportion.R                      198      11  94.44%   71-78, 82, 87, 451, 552
R/fit_rsp_step.R                              36       0  100.00%
R/fit_survival_step.R                         36       0  100.00%
R/formats.R                                  115       3  97.39%   101, 138, 148
R/g_forest.R                                 437      23  94.74%   195, 246-247, 314, 331-332, 337-338, 351, 367, 414, 445, 521, 530, 611-615, 625, 693, 696, 820
R/g_lineplot.R                               199      29  85.43%   162, 175, 203, 229-232, 309-316, 334-335, 341-351, 449, 457
R/g_step.R                                    68       1  98.53%   107
R/g_waterfall.R                               47       0  100.00%
R/h_adsl_adlb_merge_using_worst_flag.R        74       0  100.00%
R/h_biomarkers_subgroups.R                    38       0  100.00%
R/h_cox_regression.R                         110       0  100.00%
R/h_logistic_regression.R                    468       3  99.36%   197-198, 265
R/h_map_for_count_abnormal.R                  54       0  100.00%
R/h_pkparam_sort.R                            15       0  100.00%
R/h_response_biomarkers_subgroups.R           74       0  100.00%
R/h_response_subgroups.R                     171      12  92.98%   242-255
R/h_stack_by_baskets.R                        65       1  98.46%   93
R/h_step.R                                   180       0  100.00%
R/h_survival_biomarkers_subgroups.R           78       0  100.00%
R/h_survival_duration_subgroups.R            200      12  94.00%   249-261
R/incidence_rate.R                            93       7  92.47%   69-76
R/individual_patient_plot.R                  133       0  100.00%
R/kaplan_meier_plot.R                        567      61  89.24%   258-293, 302-306, 501, 668-670, 678-680, 706, 713-714, 885, 1066, 1304-1315
R/logistic_regression.R                      101       0  100.00%
R/missing_data.R                              21       3  85.71%   30, 61, 71
R/odds_ratio.R                               106       0  100.00%
R/prop_diff_test.R                            88       0  100.00%
R/prop_diff.R                                255      12  95.29%   95, 250-257, 396, 458, 567
R/prune_occurrences.R                         57      10  82.46%   130-134, 174-178
R/response_biomarkers_subgroups.R             59       0  100.00%
R/response_subgroups.R                       165       4  97.58%   262, 304-306
R/rtables_access.R                            38       4  89.47%   142-145
R/score_occurrences.R                         20       1  95.00%   114
R/split_cols_by_groups.R                      49       0  100.00%
R/stat.R                                      47       3  93.62%   76-77, 132
R/summarize_ancova.R                          95       1  98.95%   192
R/summarize_change.R                          27       0  100.00%
R/summarize_colvars.R                          6       0  100.00%
R/summarize_coxreg.R                         140       0  100.00%
R/summarize_glm_count.R                      164       4  97.56%   180, 185, 247, 316
R/summarize_num_patients.R                    68       5  92.65%   97-99, 193-194
R/summarize_patients_exposure_in_cols.R       47       0  100.00%
R/summarize_variables.R                      217       2  99.08%   269, 481
R/survival_biomarkers_subgroups.R             59       0  100.00%
R/survival_coxph_pairwise.R                   73       9  87.67%   66-74
R/survival_duration_subgroups.R              172       0  100.00%
R/survival_time.R                             47       0  100.00%
R/survival_timepoint.R                       114       7  93.86%   149-155
R/utils_checkmate.R                           68       0  100.00%
R/utils_factor.R                              87       1  98.85%   93
R/utils_grid.R                               111       5  95.50%   148, 257-263
R/utils_rtables.R                             86       7  91.86%   25, 32-36, 346-347
R/utils.R                                    137      10  92.70%   100, 102, 106, 126, 129, 132, 136, 145-146, 332
TOTAL                                       8894     353  96.03%

Diff against main

Filename      Stmts    Miss  Cover
----------  -------  ------  --------
TOTAL             0       0  +100.00%

Results for commit: 703c859

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

@shajoezhu shajoezhu self-assigned this May 2, 2023
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github-actions bot commented May 2, 2023

Unit Tests Summary

       1 files    77 suites   1m 12s ⏱️
   726 tests 726 ✔️     0 💤 0
1 541 runs  971 ✔️ 570 💤 0

Results for commit c2bb512.

♻️ This comment has been updated with latest results.

@Melkiades
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to merge after insightsengineering/rtables#619

@Melkiades Melkiades added blocked and removed blocked labels May 3, 2023
@Melkiades Melkiades requested review from edelarua and shajoezhu May 3, 2023 14:58
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Lgtm!

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@shajoezhu shajoezhu left a comment

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brilliant! Thanks @Melkiades

@Melkiades Melkiades merged commit cc870fb into main May 3, 2023
@Melkiades Melkiades deleted the 890_add_biomarker_staged@main branch May 3, 2023 15:55
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Add biomarker-catalog to staged.deps to avoid downstream breaking changes
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