survivalG: G-estimator for Cox and Fine-Gray model

In mets: Analysis of Multivariate Event Times

G-estimator for Cox and Fine-Gray model

Description

Computes G-estimator

\hat S(t,A=a) = n^{-1} ∑_i \hat S(t,A=a,Z_i)

for the Cox model based on phreg og the Fine-Gray model based on the cifreg function. Assumes that the first covariate is $A$ and this is a factor. Gives influence functions of these risk estimates and SE's are based on these.

Usage

survivalG(x, data, time = NULL)

Arguments

x	phreg or cifreg object
data	data frame for risk averaging
time	for estimate

Author(s)

Thomas Scheike

Examples

data(bmt); bmt$time <- bmt$time+runif(408)*0.001
bmt$event <- (bmt$cause!=0)*1
dfactor(bmt) <- tcell~tcell

fg1 <- cifreg(Event(time,cause)~tcell+platelet+age,bmt,cause=1,
              cox.prep=TRUE,propodds=NULL)
summary(survivalG(fg1,bmt,50))

ss <- phreg(Surv(time,event)~tcell+platelet+age,bmt) 
summary(survivalG(ss,bmt,50))

mets documentation built on Jan. 17, 2023, 5:12 p.m.