This function censors a study after a pre-specified number of events occurred.
Value
This function returns a data set that is censored after eventNum of
typeEvent-events occurred.
Examples
transition1 <- weibull_transition(h01 = 1.2, h02 = 1.5, h12 = 1.6, p01 = 0.8, p02 = 0.9, p12 = 1)
transition2 <- weibull_transition(h01 = 1, h02 = 1.3, h12 = 1.7, p01 = 1.1, p02 = 0.9, p12 = 1.1)
simStudy <- getOneClinicalTrial(
nPat = c(20, 20), transitionByArm = list(transition1, transition2),
dropout = list(rate = 0.3, time = 10),
accrual = list(param = "time", value = 7)
)
simStudyWide <- getDatasetWideFormat(simStudy)
censoringByNumberEvents(data = simStudyWide, eventNum = 20, typeEvent = "PFS")
#> id trt PFStime PFSevent OStime CensoredOS OSevent recruitTime
#> 1 1 1 0.20251761 1 0.20251761 0 1 2.0303511
#> 2 2 1 0.32225015 1 0.33107435 1 0 3.3605262
#> 3 4 1 0.02100692 1 0.02100692 0 1 2.8050413
#> 4 5 1 0.48344054 1 0.48344054 0 1 1.4922090
#> 5 7 1 1.90043827 1 1.90043827 0 1 0.4102988
#> 6 9 1 0.13622285 1 0.13622285 0 1 1.0432483
#> 7 10 1 0.06170412 0 0.06170412 1 0 3.6298964
#> 8 13 1 0.22595459 1 0.22595459 0 1 1.6891981
#> 9 16 1 0.05506586 1 0.05506586 0 1 0.1956922
#> 10 17 1 0.40591047 1 0.40591047 0 1 3.2856901
#> 11 20 1 0.59979587 1 0.59979587 0 1 2.8273770
#> 12 22 2 0.11168171 1 0.11168171 0 1 0.7045952
#> 13 25 2 0.51764752 1 0.67757502 0 1 2.6835947
#> 14 27 2 0.22308854 0 0.22308854 1 0 2.4450933
#> 15 29 2 0.25793778 1 0.25793778 0 1 1.5126998
#> 16 30 2 0.16932117 1 0.28035167 0 1 0.2246490
#> 17 31 2 0.35858824 1 1.98005050 0 1 1.0172109
#> 18 33 2 0.26420629 1 0.26420629 0 1 1.4920452
#> 19 34 2 1.08675230 1 1.29091031 0 1 1.4721752
#> 20 35 2 1.57561614 1 1.57561614 0 1 0.2766448
#> 21 37 2 1.01421133 1 1.25121844 0 1 1.7144959
#> 22 39 2 0.64035375 1 1.67394039 1 0 2.0176602
#> OStimeCal PFStimeCal
#> 1 2.2328687 2.2328687
#> 2 3.6916006 3.6827764
#> 3 2.8260482 2.8260482
#> 4 1.9756495 1.9756495
#> 5 2.3107371 2.3107371
#> 6 1.1794711 1.1794711
#> 7 3.6916006 3.6916006
#> 8 1.9151527 1.9151527
#> 9 0.2507580 0.2507580
#> 10 3.6916006 3.6916006
#> 11 3.4271729 3.4271729
#> 12 0.8162769 0.8162769
#> 13 3.3611697 3.2012422
#> 14 2.6681819 2.6681819
#> 15 1.7706376 1.7706376
#> 16 0.5050006 0.3939701
#> 17 2.9972614 1.3757991
#> 18 1.7562515 1.7562515
#> 19 2.7630855 2.5589275
#> 20 1.8522610 1.8522610
#> 21 2.9657144 2.7287072
#> 22 3.6916006 2.6580139