Conversion of a Data Set from One Row per Transition to One Row per Patient
Source:R/getClinicalTrials.R
getDatasetWideFormat.RdConversion of a Data Set from One Row per Transition to One Row per Patient
Arguments
- data
(
data.frame)
data frame containing entry and exit times of an illness-death model. SeegetSimulatedData()for details.
Details
The output data set contains the following columns:
id (
integer): patient id.trt
integer): treatment id.PFStime (
numeric): event time of PFS event.CensoredPFS (
logical): censoring indicator for PFS event.PFSevent (
logical): event indicator for PFS event.OStime (
numeric): event time of OS event.CensoredOS (
logical): censoring indicator for OS event.OSevent (
logical): event indicator for OS event.recruitTime (
numeric): time of recruitment.OStimeCal (
numeric): OS event time at calendar time scale.PFStimeCal (
numeric): PFS event time at calendar time scale.
Examples
transition1 <- exponential_transition(h01 = 1.2, h02 = 1.5, h12 = 1.6)
transition2 <- exponential_transition(h01 = 1, h02 = 1.3, h12 = 1.7)
transition3 <- exponential_transition(h01 = 1.1, h02 = 1, h12 = 1.5)
simData <- getOneClinicalTrial(
nPat = c(30, 20, 30), transitionByArm = list(transition1, transition2, transition3),
dropout = list(rate = 0, time = 12),
accrual = list(param = "time", value = 0)
)
getDatasetWideFormat(simData)
#> id trt PFStime CensoredPFS PFSevent OStime CensoredOS OSevent
#> 1 1 1 0.3223123286 0 1 0.3223123286 0 1
#> 2 2 1 0.7090484104 0 1 1.0449132260 0 1
#> 3 3 1 0.2966917416 0 1 1.8327935276 0 1
#> 4 4 1 0.0290521679 0 1 0.4014558005 0 1
#> 5 5 1 0.0984397000 0 1 0.0984397000 0 1
#> 6 6 1 0.0467190512 0 1 0.0467190512 0 1
#> 7 7 1 1.1970408702 0 1 1.1970408702 0 1
#> 8 8 1 0.0914600143 0 1 0.0914600143 0 1
#> 9 9 1 0.1740391511 0 1 0.4797561694 0 1
#> 10 10 1 0.0669849606 0 1 0.0669849606 0 1
#> 11 11 1 0.0183250973 0 1 0.0183250973 0 1
#> 12 12 1 0.0748979707 0 1 0.0748979707 0 1
#> 13 13 1 0.0378583541 0 1 1.0398236834 0 1
#> 14 14 1 0.8564882180 0 1 1.0781238692 0 1
#> 15 15 1 0.0740669305 0 1 0.5514924957 0 1
#> 16 16 1 0.2266543744 0 1 0.2266543744 0 1
#> 17 17 1 0.6146259754 0 1 0.7473521660 0 1
#> 18 18 1 0.1002014077 0 1 0.1002014077 0 1
#> 19 19 1 0.3708130248 0 1 1.1892153053 0 1
#> 20 20 1 0.5121405273 0 1 1.6026970664 0 1
#> 21 21 1 0.1249750119 0 1 0.1249750119 0 1
#> 22 22 1 0.3198303997 0 1 0.5965047805 0 1
#> 23 23 1 0.0101546944 0 1 0.0101546944 0 1
#> 24 24 1 0.0436662644 0 1 0.0436662644 0 1
#> 25 25 1 0.2434898709 0 1 0.2434898709 0 1
#> 26 26 1 0.1254999918 0 1 0.1254999918 0 1
#> 27 27 1 0.2292678100 0 1 0.2956419227 0 1
#> 28 28 1 0.4499335461 0 1 0.4499335461 0 1
#> 29 29 1 0.0007772943 0 1 0.0007772943 0 1
#> 30 30 1 1.3579126659 0 1 1.3579126659 0 1
#> 31 31 2 0.1631144539 0 1 0.8036697087 0 1
#> 32 32 2 0.1674414283 0 1 0.1674414283 0 1
#> 33 33 2 0.3812552098 0 1 1.3292929861 0 1
#> 34 34 2 0.4237612060 0 1 0.4237612060 0 1
#> 35 35 2 0.5834219837 0 1 0.6399333588 0 1
#> 36 36 2 0.2653941743 0 1 0.2653941743 0 1
#> 37 37 2 0.3727146459 0 1 0.3727146459 0 1
#> 38 38 2 0.3973146045 0 1 0.3973146045 0 1
#> 39 39 2 0.3667502014 0 1 0.3667502014 0 1
#> 40 40 2 0.0429461757 0 1 0.0429461757 0 1
#> 41 41 2 0.5443080149 0 1 0.5443080149 0 1
#> 42 42 2 0.1764437995 0 1 0.4117917707 0 1
#> 43 43 2 0.2352831257 0 1 0.2352831257 0 1
#> 44 44 2 0.0196460790 0 1 0.0271103262 0 1
#> 45 45 2 0.0804805123 0 1 0.1550929184 0 1
#> 46 46 2 0.0969404259 0 1 0.0969404259 0 1
#> 47 47 2 0.5627109950 0 1 0.6880157237 0 1
#> 48 48 2 0.9026030484 0 1 1.2719707752 0 1
#> 49 49 2 0.1235704054 0 1 0.1235704054 0 1
#> 50 50 2 0.3981708081 0 1 0.8624516616 0 1
#> 51 51 3 0.4594657688 0 1 0.4594657688 0 1
#> 52 52 3 0.1251391811 0 1 0.1262682581 0 1
#> 53 53 3 1.3438075372 0 1 1.3438075372 0 1
#> 54 54 3 0.7251947416 0 1 2.3865750257 0 1
#> 55 55 3 0.3043318314 0 1 0.6001784215 0 1
#> 56 56 3 1.1346912025 0 1 1.9114513094 0 1
#> 57 57 3 0.5212354515 0 1 0.5212354515 0 1
#> 58 58 3 0.1570238975 0 1 0.9953626874 0 1
#> 59 59 3 0.2994753927 0 1 0.3063574116 0 1
#> 60 60 3 0.4322770645 0 1 0.4322770645 0 1
#> 61 61 3 1.9834377047 0 1 2.0773792705 0 1
#> 62 62 3 1.0263111443 0 1 1.0263111443 0 1
#> 63 63 3 1.1442477067 0 1 2.6578470172 0 1
#> 64 64 3 0.9667957638 0 1 1.0897027185 0 1
#> 65 65 3 0.2497635085 0 1 0.6976538819 0 1
#> 66 66 3 0.1468731254 0 1 0.7709579604 0 1
#> 67 67 3 0.2840875130 0 1 0.7360299225 0 1
#> 68 68 3 0.1335834217 0 1 0.1335834217 0 1
#> 69 69 3 0.3219019261 0 1 0.3219019261 0 1
#> 70 70 3 0.1599954073 0 1 0.1599954073 0 1
#> 71 71 3 0.3750693657 0 1 0.3750693657 0 1
#> 72 72 3 0.2729358338 0 1 0.2729358338 0 1
#> 73 73 3 0.1604183449 0 1 0.1604183449 0 1
#> 74 74 3 0.2973777392 0 1 0.2973777392 0 1
#> 75 75 3 0.3617279388 0 1 0.3617279388 0 1
#> 76 76 3 0.7100506623 0 1 0.7100506623 0 1
#> 77 77 3 0.1327475743 0 1 0.1327475743 0 1
#> 78 78 3 0.0418417170 0 1 0.0418417170 0 1
#> 79 79 3 0.0698837055 0 1 0.0698837055 0 1
#> 80 80 3 0.5552120578 0 1 0.5552120578 0 1
#> recruitTime OStimeCal PFStimeCal
#> 1 0 0.3223123286 0.3223123286
#> 2 0 1.0449132260 0.7090484104
#> 3 0 1.8327935276 0.2966917416
#> 4 0 0.4014558005 0.0290521679
#> 5 0 0.0984397000 0.0984397000
#> 6 0 0.0467190512 0.0467190512
#> 7 0 1.1970408702 1.1970408702
#> 8 0 0.0914600143 0.0914600143
#> 9 0 0.4797561694 0.1740391511
#> 10 0 0.0669849606 0.0669849606
#> 11 0 0.0183250973 0.0183250973
#> 12 0 0.0748979707 0.0748979707
#> 13 0 1.0398236834 0.0378583541
#> 14 0 1.0781238692 0.8564882180
#> 15 0 0.5514924957 0.0740669305
#> 16 0 0.2266543744 0.2266543744
#> 17 0 0.7473521660 0.6146259754
#> 18 0 0.1002014077 0.1002014077
#> 19 0 1.1892153053 0.3708130248
#> 20 0 1.6026970664 0.5121405273
#> 21 0 0.1249750119 0.1249750119
#> 22 0 0.5965047805 0.3198303997
#> 23 0 0.0101546944 0.0101546944
#> 24 0 0.0436662644 0.0436662644
#> 25 0 0.2434898709 0.2434898709
#> 26 0 0.1254999918 0.1254999918
#> 27 0 0.2956419227 0.2292678100
#> 28 0 0.4499335461 0.4499335461
#> 29 0 0.0007772943 0.0007772943
#> 30 0 1.3579126659 1.3579126659
#> 31 0 0.8036697087 0.1631144539
#> 32 0 0.1674414283 0.1674414283
#> 33 0 1.3292929861 0.3812552098
#> 34 0 0.4237612060 0.4237612060
#> 35 0 0.6399333588 0.5834219837
#> 36 0 0.2653941743 0.2653941743
#> 37 0 0.3727146459 0.3727146459
#> 38 0 0.3973146045 0.3973146045
#> 39 0 0.3667502014 0.3667502014
#> 40 0 0.0429461757 0.0429461757
#> 41 0 0.5443080149 0.5443080149
#> 42 0 0.4117917707 0.1764437995
#> 43 0 0.2352831257 0.2352831257
#> 44 0 0.0271103262 0.0196460790
#> 45 0 0.1550929184 0.0804805123
#> 46 0 0.0969404259 0.0969404259
#> 47 0 0.6880157237 0.5627109950
#> 48 0 1.2719707752 0.9026030484
#> 49 0 0.1235704054 0.1235704054
#> 50 0 0.8624516616 0.3981708081
#> 51 0 0.4594657688 0.4594657688
#> 52 0 0.1262682581 0.1251391811
#> 53 0 1.3438075372 1.3438075372
#> 54 0 2.3865750257 0.7251947416
#> 55 0 0.6001784215 0.3043318314
#> 56 0 1.9114513094 1.1346912025
#> 57 0 0.5212354515 0.5212354515
#> 58 0 0.9953626874 0.1570238975
#> 59 0 0.3063574116 0.2994753927
#> 60 0 0.4322770645 0.4322770645
#> 61 0 2.0773792705 1.9834377047
#> 62 0 1.0263111443 1.0263111443
#> 63 0 2.6578470172 1.1442477067
#> 64 0 1.0897027185 0.9667957638
#> 65 0 0.6976538819 0.2497635085
#> 66 0 0.7709579604 0.1468731254
#> 67 0 0.7360299225 0.2840875130
#> 68 0 0.1335834217 0.1335834217
#> 69 0 0.3219019261 0.3219019261
#> 70 0 0.1599954073 0.1599954073
#> 71 0 0.3750693657 0.3750693657
#> 72 0 0.2729358338 0.2729358338
#> 73 0 0.1604183449 0.1604183449
#> 74 0 0.2973777392 0.2973777392
#> 75 0 0.3617279388 0.3617279388
#> 76 0 0.7100506623 0.7100506623
#> 77 0 0.1327475743 0.1327475743
#> 78 0 0.0418417170 0.0418417170
#> 79 0 0.0698837055 0.0698837055
#> 80 0 0.5552120578 0.5552120578