crossTime-methods: Computes the crossing survival times

In YPPE: Yang and Prentice Model with Piecewise Exponential Baseline Distribution

Description

Computes the crossing survival times

Usage

## S3 method for class 'yppe'
crossTime(object, newdata1, newdata2, conf.level = 0.95, nboot = 4000, ...)

Arguments

object	an object of class yppe
newdata1	a data frame containing the first set of explanatory variables
newdata2	a data frame containing the second set of explanatory variables
conf.level	level of the confidence/credible intervals
nboot	number of bootstrap samples (default nboot=4000); ignored if approach="bayes".
...	further arguments passed to or from other methods.

Value

the crossing survival time

Examples

# ML approach:
library(YPPE)
mle <- yppe(Surv(time, status)~arm, data=ipass, approach="mle")
summary(mle)
newdata1 <- data.frame(arm=0)
newdata2 <- data.frame(arm=1)
tcross <- crossTime(mle, newdata1, newdata2)
tcross
ekm <- survfit(Surv(time, status)~arm, data=ipass)
newdata <- data.frame(arm=0:1)
St <- survfit(mle, newdata)
time <- sort(ipass$time)
plot(ekm, col=1:2)
lines(time, St[[1]])
lines(time, St[[2]], col=2)
abline(v=tcross, col="blue")

# Bayesian approach:
bayes <- yppe(Surv(time, status)~arm, data=ipass, approach="bayes")
summary(bayes)
newdata1 <- data.frame(arm=0)
newdata2 <- data.frame(arm=1)
tcross <- crossTime(bayes, newdata1, newdata2)
tcross
ekm <- survfit(Surv(time, status)~arm, data=ipass)
newdata <- data.frame(arm=0:1)
St <- survfit(bayes, newdata)
time <- sort(ipass$time)
plot(ekm, col=1:2)
lines(time, St[[1]])
lines(time, St[[2]], col=2)
abline(v=tcross, col="blue")

YPPE documentation built on Jan. 10, 2020, 1:08 a.m.