R Under development (unstable) (2024-05-12 r86534 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(calibmsm) > > test_check("calibmsm") The method used to assess calibration was BLR-IPCW There were non-zero predicted transition probabilities into states 1,2,3,4,5,6 Calibration curves have been estimated for transitions into states 1,2,3,4,5,6 Calibration was assessed at time 1826 and calibration was assessed in a landmarked cohort of individuals in state j = 1 at time s = 0 A confidence interval was not estimated The estimated data are stored in list element `plotdata`: $state1 id pred obs 2 2 0.1140189 0.1095897 4 4 0.1383878 0.1036308 5 5 0.1233226 0.1051035 $state2 id pred obs 2 2 0.2316569 0.1698031 4 4 0.1836189 0.1855591 5 5 0.1609740 0.1759804 $state3 id pred obs 2 2 0.08442692 0.12485834 4 4 0.07579429 0.11666056 5 5 0.05508100 0.09189341 $state4 id pred obs 2 2 0.2328398 0.2427580 4 4 0.2179331 0.2243106 5 5 0.1828176 0.1851051 $state5 id pred obs 2 2 0.1481977 0.1909795 4 4 0.1538475 0.1654523 5 5 0.1425950 0.2215190 $state6 id pred obs 2 2 0.1888598 0.2069354 4 4 0.2304185 0.2542212 5 5 0.3352099 0.3163102 The method used to assess calibration was BLR-IPCW There were non-zero predicted transition probabilities into states 1,2,3,4,5,6 Calibration curves have been estimated for transitions into states 1,2,3,4,5,6 Calibration was assessed at time 1826 and calibration was assessed in a landmarked cohort of individuals in state j = 1 at time s = 0 A confidence interval was not estimated The estimated data are stored in list element `plotdata`: $state1 id pred obs 2 2 0.1140189 0.1245082 4 4 0.1383878 0.1143276 5 5 0.1233226 0.1280757 $state2 id pred obs 2 2 0.2316569 0.1693576 4 4 0.1836189 0.2008740 5 5 0.1609740 0.1509011 $state3 id pred obs 2 2 0.08442692 0.13900497 4 4 0.07579429 0.12943777 5 5 0.05508100 0.09293168 $state4 id pred obs 2 2 0.2328398 0.2097518 4 4 0.2179331 0.1871859 5 5 0.1828176 0.1985304 $state5 id pred obs 2 2 0.1481977 0.1838697 4 4 0.1538475 0.1451690 5 5 0.1425950 0.2266787 $state6 id pred obs 2 2 0.1888598 0.2048238 4 4 0.2304185 0.2302551 5 5 0.3352099 0.3267404 The method used to assess calibration was MLR-IPCW There were non-zero predicted transition probabilities into states 1,2,3,4,5,6 Calibration curves have been estimated for transitions into states 1,2,3,4,5,6 Calibration was assessed at time 1826 and calibration was assessed in a landmarked cohort of individuals in state j = 1 at time s = 0 A confidence interval was not estimated The estimated data are stored in list element `plotdata`: $state1 id pred obs 1 2 0.1140189 0.03440096 2 4 0.1383878 0.04099915 3 5 0.1233226 0.05893696 $state2 id pred obs 1 2 0.2316569 0.1780035 2 4 0.1836189 0.2657628 3 5 0.1609740 0.2526826 $state3 id pred obs 1 2 0.08442692 0.092469995 2 4 0.07579429 0.023843989 3 5 0.05508100 0.009461911 $state4 id pred obs 1 2 0.2328398 0.14599382 2 4 0.2179331 0.17808381 3 5 0.1828176 0.09505266 $state5 id pred obs 1 2 0.1481977 0.2907131 2 4 0.1538475 0.3122518 3 5 0.1425950 0.3684011 $state6 id pred obs 1 2 0.1888598 0.2584187 2 4 0.2304185 0.1790584 3 5 0.3352099 0.2154647 The method used to assess calibration was MLR-IPCW There were non-zero predicted transition probabilities into states 1,2,3,4,5,6 Calibration curves have been estimated for transitions into states 1,2,3,4,5,6 Calibration was assessed at time 1826 and calibration was assessed in a landmarked cohort of individuals in state j = 1 at time s = 0 A 95% confidence interval was estimated with bootstrapping with 5 bootstrap replicates The estimated data are stored in list element `plotdata`: list() The method used to assess calibration was Pseudo-values with Aalen-Johansen estimator There were non-zero predicted transition probabilities into states 1,2,3,4,5,6 Calibration curves have been estimated for transitions into states 1,2,3,4,5,6 Calibration was assessed at time 1826 and calibration was assessed in a landmarked cohort of individuals in state j = 1 at time s = 0 A confidence interval was not estimated The estimated data are stored in list element `plotdata`: $state1 id pred obs pv 1 1 0.1139726 0.0007884881 -0.0034597686 2 2 0.1140189 0.0008356659 0.0004375128 3 3 0.1136646 0.0005012250 -0.0053167450 $state2 id pred obs pv 1 1 0.2295006 0.2472482 1.018092475 2 2 0.2316569 0.2648225 0.002282975 3 3 0.2317636 0.2654082 -0.018205575 $state3 id pred obs pv 1 1 0.08450376 0.3425900 -0.009054339 2 2 0.08442692 0.3414199 -0.028732251 3 3 0.08274331 0.3059819 0.920938844 $state4 id pred obs pv 1 1 0.2326861 0.2251249 -0.007747993 2 2 0.2328398 0.2232169 0.014129269 3 3 0.2325663 0.2265976 0.013257306 $state5 id pred obs pv 1 1 0.1504855 0.3384060 0.00371276 2 2 0.1481977 0.3174861 1.01908125 3 3 0.1504787 0.3383704 -0.01677040 $state6 id pred obs pv 1 1 0.1888514 0.1074200 -0.001543135 2 2 0.1888598 0.1074443 -0.007198751 3 3 0.1887834 0.1072239 0.106096573 The method used to assess calibration was Pseudo-values with Aalen-Johansen estimator There were non-zero predicted transition probabilities into states 1,2,3,4,5,6 Calibration curves have been estimated for transitions into states 1,2 Calibration was assessed at time 1826 and calibration was assessed in a landmarked cohort of individuals in state j = 1 at time s = 0 A 95% confidence interval was estimated with a parametric approach The estimated data are stored in list element `plotdata`: $state1 id pred obs obs.lower obs.upper pv 1 1 0.1139726 0.0007884881 -0.1029245 0.1045015 -0.0034597686 2 2 0.1140189 0.0008356659 -0.1030055 0.1046769 0.0004375128 3 3 0.1136646 0.0005012250 -0.1023465 0.1033489 -0.0053167450 $state2 id pred obs obs.lower obs.upper pv 1 1 0.2295006 0.2472482 0.01381089 0.4806856 1.018092475 2 2 0.2316569 0.2648225 0.03932820 0.4903169 0.002282975 3 3 0.2317636 0.2654082 0.04043786 0.4903786 -0.018205575 List of 2 $ plotdata:List of 6 ..$ state1:'data.frame': 50 obs. of 5 variables: .. ..$ pred : num [1:50] 0.114 0.114 0.114 0.138 0.123 ... .. ..$ obs : num [1:50] 0.000788 0.000836 0.000501 0.055485 0.023953 ... .. ..$ obs.lower: num [1:50] -0.1029 -0.103 -0.1023 -0.0433 -0.1223 ... .. ..$ obs.upper: num [1:50] 0.105 0.105 0.103 0.154 0.17 ... .. ..$ pv : num [1:50] -0.00346 0.000438 -0.005317 0.005581 -0.00346 ... ..$ state2:'data.frame': 50 obs. of 5 variables: .. ..$ pred : num [1:50] 0.23 0.232 0.232 0.184 0.161 ... .. ..$ obs : num [1:50] 0.247 0.265 0.265 0.235 0.26 ... .. ..$ obs.lower: num [1:50] 0.0138 0.0393 0.0404 0.0421 0.0247 ... .. ..$ obs.upper: num [1:50] 0.481 0.49 0.49 0.429 0.495 ... .. ..$ pv : num [1:50] 1.01809 0.00228 -0.01821 0.00921 0.01928 ... ..$ state3:'data.frame': 50 obs. of 5 variables: .. ..$ pred : num [1:50] 0.0845 0.0844 0.0827 0.0758 0.0551 ... .. ..$ obs : num [1:50] 0.3426 0.3414 0.306 0.1044 -0.0086 ... .. ..$ obs.lower: num [1:50] 0.138 0.137 0.107 -0.192 -0.179 ... .. ..$ obs.upper: num [1:50] 0.547 0.545 0.505 0.401 0.161 ... .. ..$ pv : num [1:50] -0.00905 -0.02873 0.92094 -0.01839 -0.00905 ... ..$ state4:'data.frame': 50 obs. of 5 variables: .. ..$ pred : num [1:50] 0.233 0.233 0.233 0.218 0.183 ... .. ..$ obs : num [1:50] 0.225 0.223 0.227 0.395 0.268 ... .. ..$ obs.lower: num [1:50] 0.02097 0.01902 0.02248 0.17467 0.00874 ... .. ..$ obs.upper: num [1:50] 0.429 0.427 0.431 0.616 0.528 ... .. ..$ pv : num [1:50] -0.00775 0.01413 0.01326 -0.02199 -0.00775 ... ..$ state5:'data.frame': 50 obs. of 5 variables: .. ..$ pred : num [1:50] 0.15 0.148 0.15 0.154 0.143 ... .. ..$ obs : num [1:50] 0.338 0.317 0.338 0.333 0.239 ... .. ..$ obs.lower: num [1:50] 0.093 0.0762 0.0929 0.1159 -0.1323 ... .. ..$ obs.upper: num [1:50] 0.584 0.559 0.584 0.55 0.611 ... .. ..$ pv : num [1:50] 0.00371 1.01908 -0.01677 1.03286 1.00275 ... ..$ state6:'data.frame': 50 obs. of 5 variables: .. ..$ pred : num [1:50] 0.189 0.189 0.189 0.23 0.335 ... .. ..$ obs : num [1:50] 0.107 0.107 0.107 0.216 0.144 ... .. ..$ obs.lower: num [1:50] -0.0598 -0.0597 -0.06 0.0467 -0.069 ... .. ..$ obs.upper: num [1:50] 0.275 0.275 0.274 0.386 0.356 ... .. ..$ pv : num [1:50] -0.00154 -0.0072 0.1061 -0.00728 -0.00177 ... $ metadata:List of 10 ..$ valid.transitions : num [1:6] 1 2 3 4 5 6 ..$ assessed.transitions: num [1:6] 1 2 3 4 5 6 ..$ CI : num 95 ..$ CI.type : chr "parametric" ..$ CI.R.boot : NULL ..$ j : num 1 ..$ s : num 0 ..$ t : num 1826 ..$ calib.type : chr "pv" ..$ curve.type : chr "loess" - attr(*, "class")= chr [1:2] "calib_pv" "calib_msm" The method used to assess calibration was Pseudo-values with Aalen-Johansen estimator There were non-zero predicted transition probabilities into states 1,2,3,4,5,6 Calibration curves have been estimated for transitions into states 1,2,3,4,5,6 Calibration was assessed at time 1826 and calibration was assessed in a landmarked cohort of individuals in state j = 1 at time s = 0 A 95% confidence interval was estimated with a parametric approach The estimated data are stored in list element `plotdata`: $state1 pred obs obs.lower obs.upper pv 1 0.1139726 0.0007884881 -0.1029245 0.1045015 -0.0034597686 2 0.1140189 0.0008356659 -0.1030055 0.1046769 0.0004375128 3 0.1136646 0.0005012250 -0.1023465 0.1033489 -0.0053167450 $state2 pred obs obs.lower obs.upper pv 1 0.2295006 0.2472482 0.01381089 0.4806856 1.018092475 2 0.2316569 0.2648225 0.03932820 0.4903169 0.002282975 3 0.2317636 0.2654082 0.04043786 0.4903786 -0.018205575 $state3 pred obs obs.lower obs.upper pv 1 0.08450376 0.3425900 0.1383243 0.5468557 -0.009054339 2 0.08442692 0.3414199 0.1373466 0.5454931 -0.028732251 3 0.08274331 0.3059819 0.1065734 0.5053904 0.920938844 $state4 pred obs obs.lower obs.upper pv 1 0.2326861 0.2251249 0.02097406 0.4292758 -0.007747993 2 0.2328398 0.2232169 0.01902400 0.4274098 0.014129269 3 0.2325663 0.2265976 0.02247814 0.4307170 0.013257306 $state5 pred obs obs.lower obs.upper pv 1 0.1504855 0.3384060 0.09295346 0.5838585 0.00371276 2 0.1481977 0.3174861 0.07618096 0.5587912 1.01908125 3 0.1504787 0.3383704 0.09293268 0.5838081 -0.01677040 $state6 pred obs obs.lower obs.upper pv 1 0.1888514 0.1074200 -0.05976468 0.2746047 -0.001543135 2 0.1888598 0.1074443 -0.05973294 0.2746216 -0.007198751 3 0.1887834 0.1072239 -0.06002050 0.2744683 0.106096573 [ FAIL 0 | WARN 10 | SKIP 16 | PASS 215 ] ══ Skipped tests (16) ══════════════════════════════════════════════════════════ • On CRAN (16): 'test-calib_aj.R:106:3', 'test-calib_aj.R:158:3', 'test-calib_blr.R:135:3', 'test-calib_blr.R:264:3', 'test-calib_blr.R:318:3', 'test-calib_blr.R:462:13', 'test-calib_blr.R:507:13', 'test-calib_pv.R:8:3', 'test-calib_pv.R:221:3', 'test-calib_pv.R:273:3', 'test-calib_pv.R:326:3', 'test-calib_pv.R:480:3', 'test-calib_pv.R:523:3', 'test-calib_pv.R:554:3', 'test-calib_pv.R:584:3', 'test-calib_pv.R:615:3' [ FAIL 0 | WARN 10 | SKIP 16 | PASS 215 ] > > proc.time() user system elapsed 281.96 3.68 285.67