Collect results of a fitted prodlim object in a data.frame
# S3 method for class 'prodlim'
as.data.frame(x, ...)object obtained with function prodlim
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.
set.seed(8)
d <- SimCompRisk(17)
fit <- prodlim(Hist(time,event)~X1,data=d)
as.data.frame.prodlim(fit)
#> X1 time cause n.risk n.event n.lost absolute_risk se.absolute_risk
#> 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
#> lower upper
#> 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
as.data.frame.prodlim(fit)
#> X1 time cause n.risk n.event n.lost absolute_risk se.absolute_risk
#> 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
#> lower upper
#> 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