Simulate patients from fitted model

[gravesti]

• Implements new patient data simulation from a fitted model.
• Adds vignette describing new functionality
• Adds utility functions add_pfs() and cut_data() for detecting tumor progression and clinical cut off
• Adds example data set from clinical trial

[github-actions]

Code Coverage Summary

Filename                           Stmts    Miss  Cover    Missing
-------------------------------  -------  ------  -------  ---------------------------
R/brier_score.R                      167       0  100.00%
R/DataJoint.R                         76       0  100.00%
R/DataLongitudinal.R                 119       1  99.16%   244
R/DataSubject.R                       85       1  98.82%   142
R/DataSurvival.R                      98       0  100.00%
R/defaults.R                          10       6  40.00%   18-57, 84
R/generics.R                          36       5  86.11%   52, 382, 402, 464, 481
R/Grid.R                              27       1  96.30%   173
R/GridEven.R                          32       0  100.00%
R/GridEvent.R                         22       0  100.00%
R/GridFixed.R                         30       0  100.00%
R/GridGrouped.R                       52       0  100.00%
R/GridManual.R                        23       3  86.96%   78-80
R/GridObserved.R                      20       0  100.00%
R/GridPopulation.R                    31       4  87.10%   61, 69-71
R/GridPrediction.R                    36       6  83.33%   83, 91-95
R/JointModel.R                       131       9  93.13%   146-151, 201, 205, 247, 322
R/JointModelSamples.R                 71       0  100.00%
R/link_generics.R                     16       4  75.00%   59, 76, 91, 106
R/Link.R                              62       4  93.55%   200-203
R/LinkComponent.R                     19       3  84.21%   88, 120-121
R/LongitudinalClaretBruno.R           90       6  93.33%   168-172, 187
R/LongitudinalGSF.R                  101       0  100.00%
R/LongitudinalModel.R                 19       0  100.00%
R/LongitudinalQuantities.R            71       0  100.00%
R/LongitudinalRandomEffects.R         53      17  67.92%   80-105
R/LongitudinalRandomSlope.R           45       6  86.67%   102-106, 119
R/LongitudinalSteinFojo.R             91      10  89.01%   159-163, 194-198
R/Parameter.R                         14       0  100.00%
R/ParameterList.R                     42       1  97.62%   184
R/populationHR.R                      44       0  100.00%
R/Prior.R                            270       6  97.78%   547, 691-705
R/Promise.R                           25       0  100.00%
R/Quantities.R                        60       0  100.00%
R/QuantityGeneratorPopulation.R       22       0  100.00%
R/QuantityGeneratorPrediction.R       48       0  100.00%
R/QuantityGeneratorSubject.R          19       0  100.00%
R/settings.R                          12      12  0.00%    55-69
R/SimGroup.R                           5       0  100.00%
R/SimJointData.R                     126       6  95.24%   103, 232-236
R/SimLongitudinal.R                    5       2  60.00%   22, 40
R/SimLongitudinalClaretBruno.R        74       0  100.00%
R/SimLongitudinalGSF.R                80       0  100.00%
R/SimLongitudinalRandomSlope.R        42       0  100.00%
R/SimLongitudinalSteinFojo.R          69       0  100.00%
R/SimSurvival.R                      117       0  100.00%
R/simulate.R                         284     284  0.00%    36-451
R/StanModel.R                         15       0  100.00%
R/StanModule.R                       176       6  96.59%   192-193, 235, 246, 383, 411
R/SurvivalExponential.R               10       0  100.00%
R/SurvivalGamma.R                     13       0  100.00%
R/SurvivalLoglogistic.R               11       0  100.00%
R/SurvivalModel.R                     19       0  100.00%
R/SurvivalQuantities.R               170       1  99.41%   125
R/SurvivalWeibullPH.R                 13       0  100.00%
R/utilities.R                        144       2  98.61%   13, 335
R/zzz.R                               29      26  10.34%   4-8, 10-31, 38-47
TOTAL                               3591     432  87.97%

Diff against main

Filename            Stmts    Miss  Cover
----------------  -------  ------  --------
R/DataJoint.R           0      -2  +2.63%
R/JointModel.R         +1      -2  +1.59%
R/SimJointData.R      +54      +5  -3.37%
R/SimSurvival.R        +1       0  +100.00%
R/simulate.R         +284    +284  +100.00%
TOTAL                +340    +285  -7.51%

Results for commit: ef4a898

Minimum allowed coverage is 80%

♻️ This comment has been updated with latest results

[github-actions]

Unit Tests Summary

    1 files    191 suites   7m 4s ⏱️
  169 tests   154 ✅ 15 💤 0 ❌
1 134 runs  1 118 ✅ 16 💤 0 ❌

Results for commit ef4a898.

[github-actions]

Unit Test Performance Difference

Test Suite	$Status$	Time on main	$±Time$	$±Tests$	$±Skipped$	$±Failures$	$±Errors$
LongitudinalRandomEffects	💚	$88.72$	$-32.61$	$0$	$0$	$0$	$0$
extract_quantities	💚	$7.96$	$-7.94$	$0$	$0$	$0$	$0$
misc_models	💚	$14.41$	$-5.33$	$0$	$0$	$0$	$0$
model_multi_chain	💚	$56.40$	$-49.18$	$0$	$0$	$0$	$0$
simulate	👶		$+0.03$	$+1$	$+1$	$0$	$0$

Additional test case details

Test Suite	$Status$	Time on main	$±Time$	Test Case
Grid	💚	$112.48$	$-70.97$	Grid_objects_work_with_QuantityGenerator_and_QuantityCollapser
GridPrediction	💚	$131.20$	$-14.04$	GridPrediction_works_as_expected_for_Survival_models
JointModelSamples	💔	$11.82$	$+21.06$	print_works_as_expected_for_JointModelSamples
LongitudinalClaretBruno	💚	$1931.51$	$-1924.87$	LongitudinalClaretBruno_works_as_expected_with_default_arguments
LongitudinalGSF	💚	$1772.47$	$-1764.56$	LongitudinalGSF_works_as_expected_with_default_arguments
LongitudinalQuantiles	💚	$51.04$	$-41.06$	Test_that_LongitudinalQuantities_works_as_expected
LongitudinalRandomEffects	💚	$88.72$	$-32.61$	LongitudinalRandomEffects_works_as_expected
LongitudinalRandomSlope	💚	$59.22$	$-55.61$	Print_method_for_LongitudinalRandomSlope_works_as_expected
LongitudinalSteinFojo	💚	$1709.34$	$-1707.16$	LongitudinalSteinFojo_works_as_expected_with_default_arguments
SimJointData	👶		$+0.01$	add_pfs_works_as_expected
SimJointData	👶		$+0.00$	add_pfs_works_with_large_from_time
SimJointData	👶		$+0.00$	cut_data_works_as_expected
SimSurvival	💚	$3.05$	$-2.84$	SimSurvivalExponential_creates_a_dataset_with_the_correct_parameter
SurvivalExponential	💚	$36.39$	$-35.18$	Can_load_and_compile_SurvivalExponential_model
SurvivalGamma	💚	$210.84$	$-210.59$	Print_method_for_SurvivalGamma_works_as_expected
SurvivalLoglogistic	💚	$44.18$	$-42.88$	Can_load_and_compile_SurvivalLogLogistic_model
SurvivalQuantities	💚	$93.75$	$-37.23$	SurvivalQuantities_and_autoplot.SurvivalQuantities_works_as_expected
SurvivalWeibullPH	💚	$15.61$	$-14.16$	Print_method_for_SurvivalWeibullPH_works_as_expected
brierScore	💚	$69.96$	$-63.89$	brierScore_SurvivalQuantities_returns_same_results_as_survreg
brms_compare	💚	$342.24$	$-342.18$	jmpost_and_brms_get_similar_loo_for_longitudinal_models
extract_quantities	💚	$7.96$	$-7.94$	extract_quantities_works_as_expected
initialValues	💚	$2.78$	$-1.00$	initialValues_works_as_expected
misc_models	💚	$14.41$	$-5.33$	Longitudinal_Model_doesn_t_print_sampler_rejection_messages
model_multi_chain	💚	$56.40$	$-49.18$	Can_recover_known_distribution_parameters_from_random_slope_model_when_using_multiple_chains
populationHR	💚	$30.64$	$-10.04$	populationHR_works_as_expected_for_default_parameters
simulate	👶		$+0.11$	simulate_works_with_default_options
simulate	👶		$+0.02$	simulate_works_with_jitter_and_times
simulate	👶		$+0.03$	simulate_works_with_lambda_censor
stan_functions	💚	$37.00$	$-20.65$	GSF_SLD_function_works_as_expected

Results for commit c283172

♻️ This comment has been updated with latest results.