Collect results of a fitted prodlim object in a data.table
# S3 method for class 'prodlim'
as.data.table(x, keep.rownames = FALSE, ...)object obtained with function prodlim
Not used
passed to summary.prodlim
A data.table with the results of the prodlim object
By default object contains results for all fitted time points and all strata.
Use arguments times and newdata of summary.prodlim to subset.
library(data.table)
set.seed(8)
d <- SimCompRisk(17)
fit <- prodlim(Hist(time,event)~X1,data=d)
as.data.table(fit)
#> X1 time cause n.risk n.event n.lost absolute_risk se.absolute_risk
#> <num> <num> <char> <int> <int> <int> <num> <num>
#> 1: 0 0.0000000 1 10 0 0 0.0000000 0.0000000
#> 2: 0 0.4901679 1 10 0 1 0.0000000 0.0000000
#> 3: 0 1.6077992 1 9 0 0 0.0000000 0.0000000
#> 4: 0 2.6119345 1 9 0 0 0.0000000 0.0000000
#> 5: 0 3.3086838 1 9 0 0 0.0000000 0.0000000
#> 6: 0 3.7273358 1 8 0 0 0.0000000 0.0000000
#> 7: 0 3.8235389 1 7 0 0 0.0000000 0.0000000
#> 8: 0 3.8574973 1 7 0 1 0.0000000 0.0000000
#> 9: 0 4.2717747 1 6 0 0 0.0000000 0.0000000
#> 10: 0 4.5278894 1 6 0 0 0.0000000 0.0000000
#> 11: 0 4.7128412 1 5 0 0 0.0000000 0.0000000
#> 12: 0 5.6507783 1 4 0 0 0.0000000 0.0000000
#> 13: 0 5.8048164 1 4 0 0 0.0000000 0.0000000
#> 14: 0 6.2343624 1 4 0 0 0.0000000 0.0000000
#> 15: 0 6.3170850 1 3 1 0 0.1296296 0.1205681
#> 16: 0 6.3773456 1 2 0 0 0.1296296 0.1205681
#> 17: 0 6.6145672 1 2 1 0 0.2592593 0.1566491
#> 18: 0 6.9834973 1 1 0 0 0.2592593 NaN
#> 19: 1 0.0000000 1 7 0 0 0.0000000 0.0000000
#> 20: 1 0.4901679 1 7 0 0 0.0000000 0.0000000
#> 21: 1 1.6077992 1 7 0 1 0.0000000 0.0000000
#> 22: 1 2.6119345 1 6 0 1 0.0000000 0.0000000
#> 23: 1 3.3086838 1 5 0 0 0.0000000 0.0000000
#> 24: 1 3.7273358 1 5 0 0 0.0000000 0.0000000
#> 25: 1 3.8235389 1 5 1 0 0.2000000 0.1788854
#> 26: 1 3.8574973 1 4 0 0 0.2000000 0.1788854
#> 27: 1 4.2717747 1 4 1 0 0.4000000 0.2190890
#> 28: 1 4.5278894 1 3 0 0 0.4000000 0.2190890
#> 29: 1 4.7128412 1 3 0 0 0.4000000 0.2190890
#> 30: 1 5.6507783 1 3 0 1 0.4000000 0.2190890
#> 31: 1 5.8048164 1 2 1 0 0.7000000 0.2387467
#> 32: 1 6.2343624 1 1 0 0 0.7000000 0.2387467
#> 33: 1 6.3170850 1 1 0 0 0.7000000 0.2387467
#> 34: 1 6.3773456 1 1 0 0 0.7000000 NaN
#> 35: 1 6.6145672 1 0 0 0 NA NA
#> 36: 1 6.9834973 1 0 0 0 NA NA
#> 37: 0 0.0000000 2 10 0 0 0.0000000 0.0000000
#> 38: 0 0.4901679 2 10 0 1 0.0000000 0.0000000
#> 39: 0 1.6077992 2 9 0 0 0.0000000 0.0000000
#> 40: 0 2.6119345 2 9 0 0 0.0000000 0.0000000
#> 41: 0 3.3086838 2 9 1 0 0.1111111 0.1047566
#> 42: 0 3.7273358 2 8 1 0 0.2222222 0.1385799
#> 43: 0 3.8235389 2 7 0 0 0.2222222 0.1385799
#> 44: 0 3.8574973 2 7 0 1 0.2222222 0.1385799
#> 45: 0 4.2717747 2 6 0 0 0.2222222 0.1385799
#> 46: 0 4.5278894 2 6 1 0 0.3518519 0.1653469
#> 47: 0 4.7128412 2 5 1 0 0.4814815 0.1758988
#> 48: 0 5.6507783 2 4 0 0 0.4814815 0.1758988
#> 49: 0 5.8048164 2 4 0 0 0.4814815 0.1758988
#> 50: 0 6.2343624 2 4 1 0 0.6111111 0.1732249
#> 51: 0 6.3170850 2 3 0 0 0.6111111 0.1732249
#> 52: 0 6.3773456 2 2 0 0 0.6111111 0.1732249
#> 53: 0 6.6145672 2 2 0 0 0.6111111 0.1732249
#> 54: 0 6.9834973 2 1 1 0 0.7407407 NaN
#> 55: 1 0.0000000 2 7 0 0 0.0000000 0.0000000
#> 56: 1 0.4901679 2 7 0 0 0.0000000 0.0000000
#> 57: 1 1.6077992 2 7 0 1 0.0000000 0.0000000
#> 58: 1 2.6119345 2 6 0 1 0.0000000 0.0000000
#> 59: 1 3.3086838 2 5 0 0 0.0000000 0.0000000
#> 60: 1 3.7273358 2 5 0 0 0.0000000 0.0000000
#> 61: 1 3.8235389 2 5 0 0 0.0000000 0.0000000
#> 62: 1 3.8574973 2 4 0 0 0.0000000 0.0000000
#> 63: 1 4.2717747 2 4 0 0 0.0000000 0.0000000
#> 64: 1 4.5278894 2 3 0 0 0.0000000 0.0000000
#> 65: 1 4.7128412 2 3 0 0 0.0000000 0.0000000
#> 66: 1 5.6507783 2 3 0 1 0.0000000 0.0000000
#> 67: 1 5.8048164 2 2 0 0 0.0000000 0.0000000
#> 68: 1 6.2343624 2 1 0 0 0.0000000 0.0000000
#> 69: 1 6.3170850 2 1 0 0 0.0000000 0.0000000
#> 70: 1 6.3773456 2 1 1 0 0.3000000 NaN
#> 71: 1 6.6145672 2 0 0 0 NA NA
#> 72: 1 6.9834973 2 0 0 0 NA NA
#> X1 time cause n.risk n.event n.lost absolute_risk se.absolute_risk
#> lower upper
#> <num> <num>
#> 1: 0.00000000 0.0000000
#> 2: 0.00000000 0.0000000
#> 3: 0.00000000 0.0000000
#> 4: 0.00000000 0.0000000
#> 5: 0.00000000 0.0000000
#> 6: 0.00000000 0.0000000
#> 7: 0.00000000 0.0000000
#> 8: 0.00000000 0.0000000
#> 9: 0.00000000 0.0000000
#> 10: 0.00000000 0.0000000
#> 11: 0.00000000 0.0000000
#> 12: 0.00000000 0.0000000
#> 13: 0.00000000 0.0000000
#> 14: 0.00000000 0.0000000
#> 15: 0.00000000 0.3659387
#> 16: 0.00000000 0.3659387
#> 17: 0.00000000 0.5662859
#> 18: NaN NaN
#> 19: 0.00000000 0.0000000
#> 20: 0.00000000 0.0000000
#> 21: 0.00000000 0.0000000
#> 22: 0.00000000 0.0000000
#> 23: 0.00000000 0.0000000
#> 24: 0.00000000 0.0000000
#> 25: 0.00000000 0.5506090
#> 26: 0.00000000 0.5506090
#> 27: 0.00000000 0.8294066
#> 28: 0.00000000 0.8294066
#> 29: 0.00000000 0.8294066
#> 30: 0.00000000 0.8294066
#> 31: 0.23206501 1.0000000
#> 32: 0.23206501 1.0000000
#> 33: 0.23206501 1.0000000
#> 34: NaN NaN
#> 35: NA NA
#> 36: NA NA
#> 37: 0.00000000 0.0000000
#> 38: 0.00000000 0.0000000
#> 39: 0.00000000 0.0000000
#> 40: 0.00000000 0.0000000
#> 41: 0.00000000 0.3164302
#> 42: 0.00000000 0.4938338
#> 43: 0.00000000 0.4938338
#> 44: 0.00000000 0.4938338
#> 45: 0.00000000 0.4938338
#> 46: 0.02777797 0.6759257
#> 47: 0.13672607 0.8262369
#> 48: 0.13672607 0.8262369
#> 49: 0.13672607 0.8262369
#> 50: 0.27159659 0.9506256
#> 51: 0.27159659 0.9506256
#> 52: 0.27159659 0.9506256
#> 53: 0.27159659 0.9506256
#> 54: NaN NaN
#> 55: 0.00000000 0.0000000
#> 56: 0.00000000 0.0000000
#> 57: 0.00000000 0.0000000
#> 58: 0.00000000 0.0000000
#> 59: 0.00000000 0.0000000
#> 60: 0.00000000 0.0000000
#> 61: 0.00000000 0.0000000
#> 62: 0.00000000 0.0000000
#> 63: 0.00000000 0.0000000
#> 64: 0.00000000 0.0000000
#> 65: 0.00000000 0.0000000
#> 66: 0.00000000 0.0000000
#> 67: 0.00000000 0.0000000
#> 68: 0.00000000 0.0000000
#> 69: 0.00000000 0.0000000
#> 70: NaN NaN
#> 71: NA NA
#> 72: NA NA
#> lower upper