1301 feature request add confidence intervals for quantiles in surv time

[iaugusty]

Pull Request

Fixes #1301
@Melkiades
I'm not sure about the impact of adding new stats to an analyze function on the remainder of the code/packages.
Could you review and share your thoughts?
This is the first function for which we'd like to add extra stats, there will be more functions for which we'd like to combine the stat and it's confidence interval into 1 line.
Once we know the approach we can follow, more of these types of updates might follow.

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Unit Tests Summary

    1 files     84 suites   1m 13s ⏱️
  870 tests   859 ✅  11 💤 0 ❌
1 867 runs  1 171 ✅ 696 💤 0 ❌

Results for commit cc1f58e.

♻️ This comment has been updated with latest results.

[github-actions]

Unit Test Performance Difference

Test Suite	$Status$	Time on main	$±Time$	$±Tests$	$±Skipped$	$±Failures$	$±Errors$
analyze_vars_in_cols	💔	$2.38$	$+3.28$	$+17$	$-7$	$0$	$0$
count_occurrences	💔	$0.74$	$+1.59$	$+10$	$-8$	$0$	$0$
count_occurrences_by_grade	💔	$1.74$	$+1.09$	$+16$	$-17$	$0$	$0$
summarize_coxreg	💔	$3.80$	$+2.48$	$+13$	$-13$	$0$	$0$
summarize_num_patients	💔	$1.06$	$+1.33$	$+18$	$-16$	$0$	$0$

Additional test case details

Test Suite	$Status$	Time on main	$±Time$	Test Case
analyze_vars_in_cols	💔	$0.46$	$+1.50$	summarize_works_with_nested_analyze
summarize_coxreg	💔	$0.62$	$+1.33$	summarize_coxreg_adds_the_multivariate_Cox_regression_layer_to_rtables

Results for commit c94458d

♻️ This comment has been updated with latest results.

[github-actions]

Code Coverage Summary

Filename                                   Stmts    Miss  Cover    Missing
---------------------------------------  -------  ------  -------  ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
R/abnormal_by_baseline.R                      65       0  100.00%
R/abnormal_by_marked.R                        55       5  90.91%   93-97
R/abnormal_by_worst_grade_worsen.R           116       3  97.41%   263-265
R/abnormal_by_worst_grade.R                   60       0  100.00%
R/abnormal.R                                  43       0  100.00%
R/analyze_variables.R                        175       2  98.86%   497, 637
R/analyze_vars_in_cols.R                     176      13  92.61%   178, 221, 235-236, 244-252
R/bland_altman.R                              92       1  98.91%   46
R/combination_function.R                       9       0  100.00%
R/compare_variables.R                         84       2  97.62%   257, 316
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                          59       1  98.31%   74
R/count_missed_doses.R                        36       0  100.00%
R/count_occurrences_by_grade.R               157       2  98.73%   177, 271
R/count_occurrences.R                        116       1  99.14%   120
R/count_patients_events_in_cols.R             67       1  98.51%   60
R/count_patients_with_event.R                 62       1  98.39%   123
R/count_patients_with_flags.R                 95       1  98.95%   134
R/count_values.R                              27       0  100.00%
R/cox_regression_inter.R                     154       0  100.00%
R/cox_regression.R                           161       0  100.00%
R/coxph.R                                    167       7  95.81%   191-195, 238, 253, 261, 267-268
R/d_pkparam.R                                406       0  100.00%
R/decorate_grob.R                            113       0  100.00%
R/desctools_binom_diff.R                     621      64  89.69%   53, 88-89, 125-126, 129, 199, 223-232, 264, 266, 286, 290, 294, 298, 353, 356, 359, 362, 422, 430, 439, 444-447, 454, 457, 466, 469, 516-517, 519-520, 522-523, 525-526, 593, 604-616, 620, 663, 676, 680
R/df_explicit_na.R                            30       0  100.00%
R/estimate_multinomial_rsp.R                  50       1  98.00%   65
R/estimate_proportion.R                      205      11  94.63%   83-90, 94, 99, 320, 486
R/fit_rsp_step.R                              36       0  100.00%
R/fit_survival_step.R                         36       0  100.00%
R/formatting_functions.R                     183       2  98.91%   141, 276
R/g_forest.R                                 585      60  89.74%   240, 252-255, 260-261, 275, 277, 287-290, 335-338, 345, 414, 501, 514, 518-519, 524-525, 538, 554, 601, 632, 707, 716, 722, 741, 796-816, 819, 830, 849, 904, 907, 1042-1047
R/g_ipp.R                                    133       0  100.00%
R/g_km.R                                     350      57  83.71%   285-288, 307-309, 363-366, 400, 428, 432-475, 482-486
R/g_lineplot.R                               260      22  91.54%   204, 378-385, 424-434, 543, 551
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        73       0  100.00%
R/h_biomarkers_subgroups.R                    46       0  100.00%
R/h_cox_regression.R                         110       0  100.00%
R/h_incidence_rate.R                          45       0  100.00%
R/h_km.R                                     509      41  91.94%   137, 189-194, 287, 378, 380-381, 392-394, 413, 420-421, 423-425, 433-435, 460, 465-468, 651-654, 1108-1119
R/h_logistic_regression.R                    468       3  99.36%   203-204, 273
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           90      12  86.67%   50-55, 107-112
R/h_response_subgroups.R                     178      18  89.89%   257-270, 329-334
R/h_stack_by_baskets.R                        64       1  98.44%   89
R/h_step.R                                   180       0  100.00%
R/h_survival_biomarkers_subgroups.R           88       6  93.18%   111-116
R/h_survival_duration_subgroups.R            207      18  91.30%   259-271, 336-341
R/imputation_rule.R                           17       0  100.00%
R/incidence_rate.R                            86       7  91.86%   67-72, 152
R/logistic_regression.R                      102       0  100.00%
R/missing_data.R                              21       3  85.71%   32, 66, 76
R/odds_ratio.R                               117       0  100.00%
R/prop_diff_test.R                            91       0  100.00%
R/prop_diff.R                                265      15  94.34%   70-73, 105, 290-297, 440, 605
R/prune_occurrences.R                         57       0  100.00%
R/response_biomarkers_subgroups.R             69       6  91.30%   196-201
R/response_subgroups.R                       213       8  96.24%   100-105, 260-261
R/riskdiff.R                                  65       5  92.31%   102-105, 114
R/rtables_access.R                            38       0  100.00%
R/score_occurrences.R                         20       1  95.00%   124
R/split_cols_by_groups.R                      49       0  100.00%
R/stat.R                                      59       0  100.00%
R/summarize_ancova.R                         106       2  98.11%   183, 188
R/summarize_change.R                          74       1  98.65%   184
R/summarize_colvars.R                         10       0  100.00%
R/summarize_coxreg.R                         172       0  100.00%
R/summarize_glm_count.R                      209       3  98.56%   193-194, 490
R/summarize_num_patients.R                    93       4  95.70%   117-119, 266
R/summarize_patients_exposure_in_cols.R       96       1  98.96%   56
R/survival_biomarkers_subgroups.R             78       6  92.31%   117-122
R/survival_coxph_pairwise.R                   84      12  85.71%   51-52, 64-73
R/survival_duration_subgroups.R              211       6  97.16%   124-129
R/survival_time.R                            111       0  100.00%
R/survival_timepoint.R                       124      10  91.94%   131-140
R/utils_checkmate.R                           68       0  100.00%
R/utils_default_stats_formats_labels.R       157       0  100.00%
R/utils_factor.R                             109       2  98.17%   84, 302
R/utils_ggplot.R                             110       0  100.00%
R/utils_grid.R                               126       5  96.03%   164, 279-286
R/utils_rtables.R                            124       9  92.74%   39, 46, 403-404, 526-530
R/utils_split_funs.R                          52       2  96.15%   82, 94
R/utils.R                                    141       7  95.04%   118, 121, 124, 128, 137-138, 332
TOTAL                                      10805     473  95.62%

Diff against main

Filename                                  Stmts    Miss  Cover
--------------------------------------  -------  ------  --------
R/analyze_variables.R                        +9       0  +0.06%
R/survival_coxph_pairwise.R                  +5      +1  -0.36%
R/survival_time.R                           +32       0  +100.00%
R/survival_timepoint.R                      +11      +3  -1.87%
R/utils_default_stats_formats_labels.R      +12       0  +100.00%
TOTAL                                       +69      +4  -0.01%

Results for commit: cc1f58e

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

[iaugusty]

I have read the CLA Document and I hereby sign the CLA

[Melkiades]

Looks very good! Thanks. Just a couple of comments (could you also add NEWS entry ;))

[Melkiades]

Pull Request

Fixes #1301 @Melkiades I'm not sure about the impact of adding new stats to an analyze function on the remainder of the code/packages. Could you review and share your thoughts? This is the first function for which we'd like to add extra stats, there will be more functions for which we'd like to combine the stat and it's confidence interval into 1 line. Once we know the approach we can follow, more of these types of updates might follow.

For the moment, it looks good. I will check downstream if there are breaking changes due to using all possible values by default but in principle that should be changed. @shajoezhu @edelarua, what do you think about freely adding stats like this?

@iaugusty, we are already trying to introduce a bit more flexibility in custom stats' addition, so for me, it is practically good to go. Lets hear the others ;)

[edelarua]

@edelarua, what do you think about freely adding stats like this?

Sounds fine to me, I would just try to stick with naming conventions used throughout the package as much as possible for any added statistics :)

[Melkiades]

Lgtm anyway! @iaugusty could you just fix the checks? Thanks

[shajoezhu]

block this PR by #1311

[Melkiades]

@iaugusty could you update the snapshots please? Thanks!!

[iaugusty]

@iaugusty could you update the snapshots please? Thanks!!

When I try to run the tests, it seems I have to update the svg files for the graphs, for font changes? Should I have some special settings to ensure I match the fonts that are being used at your end?

I added the long version also to s_summary.numeric, as median_long was added to utils_default_stats_formats_labels.R, and this is being utilized by s_summary.numeric as well. This triggered me to add this stat in s_summary.numeric, and as we want the same long version for mean there as well, I added it at the same time.
I hope this is fine within this same branch.

[Melkiades]

@iaugusty could you update the snapshots please? Thanks!!

When I try to run the tests, it seems I have to update the svg files for the graphs, for font changes? Should I have some special settings to ensure I match the fonts that are being used at your end?

I added the long version also to s_summary.numeric, as median_long was added to utils_default_stats_formats_labels.R, and this is being utilized by s_summary.numeric as well. This triggered me to add this stat in s_summary.numeric, and as we want the same long version for mean there as well, I added it at the same time. I hope this is fine within this same branch.

You can turn off the plot diff with the following (in test/setup.R):

# expect_snapshot_ggplot - set custom plot dimensions
expect_snapshot_ggplot <- function(title, fig, width = NA, height = NA) {
  testthat::skip()
  testthat::skip_on_ci()
  testthat::skip_if_not_installed("svglite")

Looking now at mean_long etc I think it would be better to have mean_ci etc as it is exactly that. Thanks Ilse!!

mean_ci is already in, which is just the CI of the mean, not including the mean, while mean_long is a 3-d stat: mean + CI

[iaugusty]

@Melkiades : not sure if you saw my reply on your comment
Looking now at mean_long etc I think it would be better to have mean_ci etc as it is exactly that. Thanks Ilse!!

mean_ci is already in, which is just the CI of the mean, not including the mean, while mean_long is a 3-d stat: mean + CI

[Melkiades]

@Melkiades : not sure if you saw my reply on your comment Looking now at mean_long etc I think it would be better to have mean_ci etc as it is exactly that. Thanks Ilse!!

mean_ci is already in, which is just the CI of the mean, not including the mean, while mean_long is a 3-d stat: mean + CI

I see! I would call it mean_and_ci or mean_ci_3d then ;)

[shajoezhu]

hi @iaugusty , I was wondering if you could update and resolve this conflict please? the PR is mostly fine to be merged now. Thanks!

[shajoezhu]

hi @iaugusty , I was wondering could you do the following please.

1. resolve the conflict
2. in https://github.com/insightsengineering/scda.test, on branch 1301-feature-request-add-confidence-intervals-for-quantiles-in-surv_time, so the test will kick off (1301 feature request add confidence intervals for quantiles in surv time scda.test#157 I have done this for you. lets wait and see)

[Melkiades]

hi @iaugusty , I was wondering could you do the following please.

1. resolve the conflict
2. in https://github.com/insightsengineering/scda.test, on branch 1301-feature-request-add-confidence-intervals-for-quantiles-in-surv_time, so the test will kick off (1301 feature request add confidence intervals for quantiles in surv time scda.test#157 I have done this for you. lets wait and see)

tests pass!! @iaugusty could you rerun the documentation to solve conflict? thanks :) then we merge