Subgroup Treatment Effect — subgroups • bonsaiforest

Function to obtain the estimated treatment effect in each one of the considered subgroups.

Usage

subgroups(object, est_coef, h0 = NULL, gamma = 1)

Arguments

object: (bonsaiforest)
the fitted bonsaiforest object.
est_coef: (matrix)
the estimated coefficients from the fitted model.
h0: (numeric)
the vector with the cumulative baseline hazard. Present just for resptype survival.
gamma: (scalar)
numeric value defining the weights to obtain the average hazard ratio. Default is 1 (in this case the average hazard ratio obtained can be interpreted as the odds of concordance).

Value

data.frame with the subgroup names and with the estimated subgroup treatment effects.

Examples

subgroups(
  elastic_net_fit_surv, elastic_net_surv$est_coef,
  elastic_net_surv$h0
)
#>    subgroup trt.estimate
#> 1      x_1a    0.6500483
#> 2      x_1b    0.6493824
#> 3      x_2a    0.6493749
#> 4      x_2b    0.6501893
#> 5      x_3a    0.6497598
#> 6      x_3b    0.6489794
#> 7      x_4a    0.6474298
#> 8      x_4b    0.6467309
#> 9      x_4c    0.6467375
#> 10     x_5a    0.6497693
#> 11     x_5b    0.6495787
#> 12     x_5c    0.6493530
#> 13     x_5d    0.6489952
#> 14     x_6a    0.6485965
#> 15     x_6b    0.6494347
#> 16     x_7a    0.6489064
#> 17     x_7b    0.6498076
#> 18     x_8a    0.6496933
#> 19     x_8b    0.6495582
#> 20     x_8c    0.6499395
#> 21     x_9a    0.6487417
#> 22     x_9b    0.6497883
#> 23    x_10a    0.6498012
#> 24    x_10b    0.6495769
#> 25    x_10c    0.6492702