120 issues

[audreyyeoCH]

closes #120

[github-actions]

Code Coverage Summary

Filename                 Stmts    Miss  Cover    Missing
---------------------  -------  ------  -------  -----------
R/betadiff.R                78       0  100.00%
R/boundsPostprob.R          44       0  100.00%
R/boundsPredprob.R          56       1  98.21%   83
R/dbetabinom.R              99       3  96.97%   32, 62, 154
R/oc2.R                    162     162  0.00%    93-326
R/oc3.R                    146     146  0.00%    91-308
R/ocPostprob.R             117       0  100.00%
R/ocPostprobDist.R         122       0  100.00%
R/ocPredprob.R             205       0  100.00%
R/ocPredprobDist.R         257       5  98.05%   363-367
R/ocRctPostprobDist.R      174       0  100.00%
R/ocRctPredprobDist.R      302       0  100.00%
R/plotBeta.R                97       9  90.72%   124-132
R/plotBounds.R              52      52  0.00%    33-90
R/plotDecision.R            73       0  100.00%
R/plotOc.R                  55       2  96.36%   99-100
R/postprob.R                34       1  97.06%   113
R/postprobDist.R            77       1  98.70%   204
R/predprob.R                36       0  100.00%
R/predprobDist.R           140       1  99.29%   269
R/runShinyPhase1b.R          4       4  0.00%    8-13
R/sumBetaDiff.R             80      15  81.25%   102-120
R/sumTable.R                36       0  100.00%
TOTAL                     2446     402  83.57%

Diff against main

Filename          Stmts    Miss  Cover
--------------  -------  ------  --------
R/dbetabinom.R       +8       0  +0.27%
R/predprob.R        +12       0  +100.00%
TOTAL               +20       0  +0.14%

Results for commit: ab6746a

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

[github-actions]

Unit Test Performance Difference

Test Suite	$Status$	Time on main	$±Time$	$±Tests$	$±Skipped$	$±Failures$	$±Errors$
ocPostprob	💚	$24.98$	$-1.43$	$0$	$0$	$0$	$0$
ocPredprob	💚	$191.52$	$-1.02$	$0$	$0$	$0$	$0$
ocPredprobDist	💚	$93.27$	$-10.39$	$0$	$0$	$0$	$0$
ocRctPredprobDist	💚	$28.29$	$-2.95$	$0$	$0$	$0$	$0$
plotOc	💚	$207.05$	$-20.88$	$0$	$0$	$0$	$0$
predprobDist	💔	$1.13$	$+20.62$	$+2426$	$0$	$0$	$0$

Additional test case details

Test Suite	$Status$	Time on main	$±Time$	Test Case
ocPredprob	💚	$188.90$	$-1.04$	ocPredprob_correctly_shows_maximum_sample_size_when_no_decision_reached
ocPredprobDist	💚	$24.32$	$-2.74$	ocPredprobDist_gives_higher_PrEfficacy_with_more_efficacy_looks
ocPredprobDist	💚	$59.97$	$-6.68$	ocPredprobDist_gives_higher_PrFutility_with_more_futility_looks
ocRctPredprobDist	💚	$11.31$	$-1.23$	ocRctPredprobDist_gives_higher_PrEfficacy_with_increased_pE
ocRctPredprobDist	💚	$11.22$	$-1.10$	ocRctPredprobDist_gives_higher_PrFutility_with_decreased_pE
plotOc	💚	$55.64$	$-6.12$	h_get_dataframe_oc_gives_correct_results_for_ocPredprobDist_when_relativeDelta_FALSE
plotOc	💚	$47.84$	$-5.23$	h_get_dataframe_oc_gives_correct_results_for_ocPredprobDist_when_relativeDelta_TRUE
plotOc	💚	$100.63$	$-9.30$	plotOc_gives_expected_results_for_ocPredprobDist_with_different_relativeDelta_status
postprob	👶		$+0.01$	postprob_from_beta_mixture_priors_utilise_updated_weights
predprob	👶		$+0.01$	Warning_length_equal_to_length_of_x
predprob	💀	$0.02$	$-0.02$	predprob_gives_correct_list
predprobDist	💔	$0.18$	$+1.77$	h_predprobdist_gives_correct_list
predprobDist	💔	$0.32$	$+5.32$	h_predprobdist_gives_higher_predictive_probability_when_thetaT_is_lower
predprobDist	💔	$0.31$	$+9.26$	predprobDist_gives_higher_predictive_probability_when_thetaT_is_lower_in_a_single_arm_trial
predprobDist	💔	$0.17$	$+3.75$	predprobDist_gives_the_correct_results_in_a_two_arm_study

Results for commit 31d6238

♻️ This comment has been updated with latest results.

[github-actions]

Unit Tests Summary

    1 files     20 suites   8m 57s ⏱️
  140 tests   140 ✅ 0 💤 0 ❌
3 764 runs  3 764 ✅ 0 💤 0 ❌

Results for commit ab6746a.

♻️ This comment has been updated with latest results.

[danielinteractive]

Thanks @audreyyeoCH , please see my comments below

[audreyyeoCH]

@danielinteractive, when users don't assign weights to two pairs of alpha and betas, then a weight of 1 is assigned to each pair, making the sum(weights) != 1. The warning will therefore come up. Is this valuable ?

[danielinteractive]

@audreyyeoCH no that would be confusing, but I guess that should be easy to fix on the package side? in the sense that we can default the weights not to 1 but to 1/nComponents ?

[audreyyeoCH]

@audreyyeoCH no that would be confusing, but I guess that should be easy to fix on the package side? in the sense that we can default the weights not to 1 but to 1/nComponents ?

Great, thanks, would it be good to move this too into h_getBetamixPost() instead of getting the user facing function to do it ?

[danielinteractive]

no, better keep the position of assigning default weights in the user facing functions

[audreyyeoCH]

no, better keep the position of assigning default weights in the user facing functions

alright, thanks!

[audreyyeoCH]

no, better keep the position of assigning default weights in the user facing functions

also for predprob when we put the warning in the helper, testing is (now passing) rather complicated as expect_warning() only refers to the first warning, but this is "solved" when we put it in the user facing function. I've found a way now, but do we still keep it in the helper ?

[danielinteractive]

the warning should stay in the helper function, because there the renormalization is done.