Convert scalib object into a flat data.table containing
input and output data.
# S3 method for scalib
as.data.table(x, ...)An object of class scalib (see scalib).
currently not used
a data.table object
library(data.table)
sc <- scalib(pred_risk = pbc_scalib$predrisk,
pred_horizon = 2500,
event_time = pbc_scalib$test$time,
event_status = pbc_scalib$test$status)
print(sc)
#>
#> Survival calibration object with prediction horizon of 2500
#>
#> -- Input data ----------------------------------------------------------------
#>
#> event_time event_status prop_hazard rsf_axis gradient_booster rsf_oblique
#> <int> <num> <num> <num> <num> <num>
#> 1: 400 1 0.9990 0.9026 0.9351 0.9463
#> 2: 4500 0 0.4272 0.3072 0.0524 0.3680
#> 3: 1925 1 0.8286 0.4722 0.2342 0.5982
#> 4: 1832 0 0.0358 0.1474 0.0422 0.1460
#> 5: 2466 1 0.0392 0.1925 0.0568 0.1558
#> ---
#> 134: 1300 0 0.1509 0.1783 0.0629 0.1669
#> 135: 1293 0 0.1805 0.3466 0.1299 0.2416
#> 136: 1250 0 0.9823 0.4743 0.3254 0.5727
#> 137: 1230 0 0.0182 0.0589 0.0322 0.0637
#> 138: 1153 0 0.0718 0.1637 0.0527 0.1220
as.data.table(sc)
#> ._id_. pred_horizon inputs
#> 1: prop_hazard 2500 <data.table[138x3]>
#> 2: rsf_axis 2500 <data.table[138x3]>
#> 3: gradient_booster 2500 <data.table[138x3]>
#> 4: rsf_oblique 2500 <data.table[138x3]>
sc_gnd <- scalib_gnd(sc)
as.data.table(sc_gnd)
#> ._id_. pred_horizon inputs outputs
#> 1: prop_hazard 2500 <data.table[138x3]> <data.table[1x5]>
#> 2: rsf_axis 2500 <data.table[138x3]> <data.table[1x5]>
#> 3: gradient_booster 2500 <data.table[138x3]> <data.table[1x5]>
#> 4: rsf_oblique 2500 <data.table[138x3]> <data.table[1x5]>