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Add analyze_patients_exposure_in_cols #916

Merged
merged 12 commits into from
May 15, 2023
Merged

Add analyze_patients_exposure_in_cols #916

merged 12 commits into from
May 15, 2023

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edelarua
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Closes #915

@edelarua edelarua added the sme label May 12, 2023
@edelarua edelarua mentioned this pull request May 12, 2023
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This was referenced May 12, 2023
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github-actions bot commented May 12, 2023 •
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Unit Tests Summary

       1 files    78 suites   55s ⏱️
   729 tests 729 ✔️     0 💤 0 ❌
1 546 runs  973 ✔️ 573 💤 0 ❌

Results for commit 0a23b78.

♻️ This comment has been updated with latest results.

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github-actions bot commented May 12, 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%   124-128
R/abnormal_by_worst_grade_worsen.R           113       3  97.35%   233-235
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%   113
R/combination_function.R                       9       0  100.00%
R/compare_variables.R                        138       3  97.83%   132, 235, 254
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%   60
R/count_missed_doses.R                        31       0  100.00%
R/count_occurrences_by_grade.R                84       6  92.86%   156-158, 161, 176-177
R/count_occurrences.R                         61       1  98.36%   92
R/count_patients_events_in_cols.R             67       1  98.51%   73
R/count_patients_with_event.R                 33       0  100.00%
R/count_patients_with_flags.R                 39       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                                    169       9  94.67%   19-20, 228-232, 277, 292, 300, 306-307
R/d_pkparam.R                                406       0  100.00%
R/decorate_grob.R                            167      38  77.25%   237-268, 279, 377, 399-436
R/desctools_binom_diff.R                     663      66  90.05%   68, 103-104, 144-145, 148, 227, 253-262, 301, 303, 323, 327, 331, 335, 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%   58
R/estimate_proportion.R                      198      11  94.44%   75-82, 86, 91, 462, 567
R/fit_rsp_step.R                              36       0  100.00%
R/fit_survival_step.R                         36       0  100.00%
R/formatting_functions.R                     115       3  97.39%   107, 145, 155
R/g_forest.R                                 437      23  94.74%   197, 248-249, 316, 333-334, 339-340, 353, 369, 416, 447, 523, 532, 613-617, 627, 697, 700, 824
R/g_lineplot.R                               199      29  85.43%   160, 173, 201, 227-230, 307-314, 332-333, 339-349, 445, 453
R/g_step.R                                    68       1  98.53%   108
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%   206-207, 276
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%   258-271
R/h_stack_by_baskets.R                        65       1  98.46%   96
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%   260-272
R/incidence_rate.R                            93       7  92.47%   68-75
R/individual_patient_plot.R                  133       0  100.00%
R/kaplan_meier_plot.R                        567      61  89.24%   248-283, 292-296, 493, 667-669, 677-679, 705, 712-713, 891, 1077, 1327-1338
R/logistic_regression.R                      101       0  100.00%
R/missing_data.R                              21       3  85.71%   32, 66, 76
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%   98, 259-266, 408, 470, 579
R/prune_occurrences.R                         57      10  82.46%   141-145, 191-195
R/response_biomarkers_subgroups.R             59       0  100.00%
R/response_subgroups.R                       165       4  97.58%   279, 321-323
R/rtables_access.R                            38       4  89.47%   163-166
R/score_occurrences.R                         20       1  95.00%   123
R/split_cols_by_groups.R                      49       0  100.00%
R/stat.R                                      47       3  93.62%   78-79, 136
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%   188, 193, 258, 327
R/summarize_num_patients.R                    68       5  92.65%   98-100, 204-205
R/summarize_patients_exposure_in_cols.R       79       0  100.00%
R/summarize_variables.R                      217       2  99.08%   275, 493
R/survival_biomarkers_subgroups.R             59       0  100.00%
R/survival_coxph_pairwise.R                   73       9  87.67%   65-73
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%   150-156
R/utils_checkmate.R                           68       0  100.00%
R/utils_factor.R                              87       1  98.85%   92
R/utils_grid.R                               111       5  95.50%   153, 265-271
R/utils_rtables.R                             86       7  91.86%   25, 32-36, 351-352
R/utils.R                                    137      10  92.70%   101, 103, 107, 129, 132, 135, 139, 148-149, 337
TOTAL                                       8927     387  95.66%

Diff against main

Filename                                   Stmts    Miss  Cover
---------------------------------------  -------  ------  --------
R/summarize_patients_exposure_in_cols.R      +32       0  +100.00%
TOTAL                                        +32       0  +0.02%

Results for commit: 81856a6

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

Melkiades
Melkiades reviewed May 13, 2023
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Melkiades
Melkiades approved these changes May 13, 2023
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@Melkiades Melkiades left a comment

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Lgtm! Thank you a lot Emily :). Only check if the examples are well representative (e.g. not too many repetitions).

@clarkliming
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I tried with the following layout

basic_table() %>%
  summarize_patients_exposure_in_cols(var = "AVAL", col_split = TRUE) %>%
  #analyze_patients_exposure_in_cols(col_split = TRUE) %>%
  analyze_patients_exposure_in_cols(var = "AVALCAT1", col_split = TRUE) %>%
  build_table(adex, adsl)

trying to create both the overall line and the splitted line. went into issue like error in evaluating the argument 'obj' in selecting a method for function 'spl_payload': subscript out of bounds

@shajoezhu
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hi @clarkliming , use "col_split = FALSE" will work

> adsl = scda.2022::rcd_2022_01_28_adsl
> adex = scda.2022::rcd_2022_01_28_adex
> basic_table() %>%
+     summarize_patients_exposure_in_cols(var = "AVAL", col_split = TRUE) %>%
+     #analyze_patients_exposure_in_cols(col_split = ) %>%
+     analyze_patients_exposure_in_cols(var = "SEX", col_split = FALSE) %>%
+     build_table(df, adsl)
                                     Patients    Person time
————————————————————————————————————————————————————————————
Total patients numbers/person time   12 (3.0%)       114    
  Female                             6 (1.5%)        46     
  Male                               6 (1.5%)        68

@clarkliming
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hi @clarkliming , use "col_split = FALSE" will work

> adsl = scda.2022::rcd_2022_01_28_adsl
> adex = scda.2022::rcd_2022_01_28_adex
> basic_table() %>%
+     summarize_patients_exposure_in_cols(var = "AVAL", col_split = TRUE) %>%
+     #analyze_patients_exposure_in_cols(col_split = ) %>%
+     analyze_patients_exposure_in_cols(var = "SEX", col_split = FALSE) %>%
+     build_table(df, adsl)
                                     Patients    Person time
————————————————————————————————————————————————————————————
Total patients numbers/person time   12 (3.0%)       114    
  Female                             6 (1.5%)        46     
  Male                               6 (1.5%)        68

thank you. I tried and it works well!

shajoezhu
shajoezhu approved these changes May 15, 2023
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Thanks so much! @edelarua for the fast turn around!

@shajoezhu shajoezhu self-assigned this May 15, 2023
@shajoezhu shajoezhu mentioned this pull request May 15, 2023
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@Melkiades Melkiades enabled auto-merge (squash) May 15, 2023 08:39
@Melkiades Melkiades merged commit c64ee78 into main May 15, 2023
@Melkiades Melkiades deleted the 915_refactor_exposure@main branch May 15, 2023 08:43
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@clarkliming clarkliming clarkliming left review comments

@shajoezhu shajoezhu shajoezhu approved these changes

@Melkiades Melkiades Melkiades approved these changes

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Create analyze counterpart for summarize_patients_exposure_in_cols
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@edelarua @clarkliming @shajoezhu @Melkiades