Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

799 Fix summarize_num_patients labels #800

Merged
merged 3 commits into from
Jan 18, 2023
Merged

799 Fix summarize_num_patients labels #800

merged 3 commits into from
Jan 18, 2023

Conversation

edelarua
Copy link
Contributor

@edelarua edelarua commented Jan 17, 2023 •
edited
Loading

Closes #799

Unblocks insightsengineering/chevron#345

Also updates default format to fixed decimal places in line with other tern functions.

@github-actions
Copy link
Contributor

github-actions bot commented Jan 17, 2023 •
edited
Loading

Unit Tests Summary

       1 files     129 suites   3m 43s ⏱️
   877 tests    877 ✔️ 0 💤 0 ❌
1 372 runs  1 372 ✔️ 0 💤 0 ❌

Results for commit fc9dda7.

♻️ This comment has been updated with latest results.

@edelarua edelarua enabled auto-merge (squash) January 17, 2023 22:33
@github-actions
Copy link
Contributor

badge

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%   205-207
R/abnormal_by_worst_grade.R                   37       0  100.00%
R/abnormal.R                                  40       0  100.00%
R/analyze_vars_in_cols.R                      37       0  100.00%
R/combination_function.R                       9       0  100.00%
R/compare_variables.R                        138       3  97.83%   135, 247, 266
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%   52
R/count_missed_doses.R                        31       0  100.00%
R/count_occurrences_by_grade.R                84       3  96.43%   148, 163-164
R/count_occurrences.R                         61       1  98.36%   89
R/count_patients_events_in_cols.R             67       0  100.00%
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                           318       0  100.00%
R/coxph.R                                    168       7  95.83%   232-236, 281, 297, 306, 312-313
R/d_pkparam.R                                405       0  100.00%
R/decorate_grob.R                            167       6  96.41%   271-277, 384, 416, 426, 433
R/desctools_binom_diff.R                     668      68  89.82%   65, 100-101, 141-142, 145, 224, 250-261, 300, 302, 322, 326, 330, 334, 386, 389, 392, 395, 456, 464, 476-477, 483-486, 494, 497, 506, 509, 557-558, 560-561, 563-564, 566-567, 640, 652-665, 670, 717, 730, 734
R/df_explicit_na.R                            30       0  100.00%
R/estimate_multinomial_rsp.R                  47       1  97.87%   53
R/estimate_proportion.R                      198      10  94.95%   421-428, 432, 437, 545
R/fit_rsp_step.R                              36       0  100.00%
R/fit_survival_step.R                         36       0  100.00%
R/footnotes.R                                  5       0  100.00%
R/formats.R                                  115       3  97.39%   101, 138, 148
R/g_forest.R                                 441      42  90.48%   172, 200, 229, 252-253, 257-258, 326, 339, 343-344, 349-350, 363, 379, 426, 457, 533, 542, 614-634, 637, 648, 705, 708, 834
R/g_lineplot.R                               199      29  85.43%   177, 190, 218, 244-247, 324-331, 349-350, 356-366, 464, 472
R/g_step.R                                    68       1  98.53%   106
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_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%   248-261
R/h_stack_by_baskets.R                        65       2  96.92%   96, 143
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%   254-266
R/incidence_rate.R                            93       7  92.47%   69-76
R/individual_patient_plot.R                  133       0  100.00%
R/kaplan_meier_plot.R                        532      29  94.55%   256-260, 456, 627-629, 637-639, 665, 672-673, 845, 1030, 1272-1283
R/logistic_regression.R                      569       3  99.47%   279-280, 347
R/missing_data.R                              20       3  85.00%   29, 61, 71
R/odds_ratio.R                               106       0  100.00%
R/prop_diff_test.R                            87       0  100.00%
R/prop_diff.R                                255      11  95.69%   56-63, 190, 364, 508
R/prune_occurrences.R                         57       0  100.00%
R/response_biomarkers_subgroups.R             59       0  100.00%
R/response_subgroups.R                       164       0  100.00%
R/rtables_access.R                            36       0  100.00%
R/score_occurrences.R                         20       1  95.00%   119
R/split_cols_by_groups.R                      49       0  100.00%
R/stat.R                                      47       0  100.00%
R/summarize_ancova.R                          95       1  98.95%   198
R/summarize_change.R                          27       0  100.00%
R/summarize_colvars.R                          6       0  100.00%
R/summarize_glm_count.R                      164       4  97.56%   169, 174, 237, 306
R/summarize_num_patients.R                    65       5  92.31%   92-94, 185-186
R/summarize_patients_exposure_in_cols.R       46       0  100.00%
R/summarize_variables.R                      212       1  99.53%   477
R/survival_biomarkers_subgroups.R             59       0  100.00%
R/survival_coxph_pairwise.R                   73       9  87.67%   69-77
R/survival_duration_subgroups.R              171       0  100.00%
R/survival_time.R                             47       0  100.00%
R/survival_timepoint.R                       114       7  93.86%   147-153
R/utils_checkmate.R                           68       0  100.00%
R/utils_factor.R                              86       1  98.84%   93
R/utils_grid.R                               111       5  95.50%   150, 260-266
R/utils_rtables.R                             84       2  97.62%   344-345
R/utils.R                                    137      10  92.70%   100, 102, 106, 126, 129, 132, 136, 145-146, 334
R/wrap_text.R                                 66       5  92.42%   39, 60, 80, 87, 109
TOTAL                                       8827     314  96.44%

Diff against main

Filename                      Stmts    Miss  Cover
--------------------------  -------  ------  -------
R/summarize_num_patients.R       +4      +2  -2.77%
TOTAL                            +4      +2  -0.02%

Results for commit: 14c0953

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

shajoezhu
shajoezhu approved these changes Jan 18, 2023
View reviewed changes
Copy link
Contributor

@shajoezhu shajoezhu left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

lgtm! Thanks a lot! @edelarua

@edelarua edelarua merged commit 1f2f647 into main Jan 18, 2023
@edelarua edelarua deleted the 799_sum_patients_labels@main branch January 18, 2023 00:28
shajoezhu
shajoezhu reviewed Jan 18, 2023
View reviewed changes
R/summarize_num_patients.R
.labels = c(
unique = "Number of patients with at least one event",
nonunique = "Number of events"
),
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@edelarua , do we need a label for ”unique_count“？

shajoezhu
shajoezhu reviewed Jan 18, 2023
View reviewed changes
R/summarize_num_patients.R
.labels = c(
unique = "Number of patients with at least one event",
nonunique = "Number of events"
),
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@edelarua , do we need a label for ”unique_count“？

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

@shajoezhu there's no label currently for unique_count, but I could add one. Do you have any preference? We could just do "Number of patients with at least one event (n)".

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Reviewers

@shajoezhu shajoezhu shajoezhu approved these changes

Assignees
No one assigned
Labels
enhancement sme
Projects
None yet
Milestone
No milestone
Development

Successfully merging this pull request may close these issues.

Fix label formatting in summarize_num_patients and analyze_num_patients
2 participants
@edelarua @shajoezhu