summary.elastic_net: Summary Elastic Net Function

In bonsaiforest: Shrinkage Based Forest Plots

Summary Elastic Net Function

Description

Function to obtain the naive subgroup treatment effects of an object fitted with the elastic_net function.

Usage

## S3 method for class 'elastic_net'
summary(object, gamma = 1, l = NULL, lambda = NULL, ...)

Arguments

object	(elastic_net) the elastic_net object.
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). Just needed when using survival data.
l	(scalar) the maximum value of time that wants to be studied to obtain the average hazard ratio. Default is the maximum value of time when there was an event. Just needed when using survival data.
lambda	(scalar) the penalization constant in the elastic net. Default is the value that leads to minimal cross validation error.
...	Arguments of summary

Value

Object of class summary.elastic_net which is a list with the estimated subgroup treatment effects, the resptype, the confidence level and the value of alpha.

Examples

summary(elastic_net_fit_surv)

bonsaiforest documentation built on Sept. 30, 2024, 9:46 a.m.