survscreen.template: Wrapper functions for screening algorithms in...

In tedwestling/survSuperLearner: Super Learning for Conditional Survival Functions with Right-Censored Data

Wrapper functions for screening algorithms in survSuperLearner

Description

This is a template function for a survSuperLearner screening algorithm. You can use this to write your own screening algorithms.

Usage

survscreen.template(time, event, X, obsWeights, id, ...)

Arguments

time	Observed follow-up time; i.e. minimum of the event and censoring times.
event	Observed event indicator; i.e, whether the follow-up time corresponds to an event or censoring.
X	Training covariate data.frame.
obsWeights	Observation weights.
id	Observation clusters.
...	Additional ignored arguments.

Value

Logical vector of the same length as the number of columns as X indicating which variables should be included.

tedwestling/survSuperLearner documentation built on Dec. 12, 2024, 4:16 p.m.