survSL.pchreg: Wrapper function for piecewise constant hazard regression

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

Wrapper function for piecewise constant hazard regression

Description

These prediciton algorithm use the pchreg function from the pch package to estimate piecewise constant hazard regressions.

Usage

survSL.pchreg(time, event, X, newX, new.times, obsWeights, breaks = 4, ...)

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.
newX	Test covariate data.frame to use for prediction. Should have the same variable names and structure as X.
new.times	Times at which to obtain to obtain the predicted survivals.
obsWeights	Observation weights.
breaks	Number or numeric vector of breaks to be passed to pchreg.
...	Additional ignored arguments.

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