wKendall: Weighted conditional Kendall's tau

In tranSurv: Transformation Model Based Estimation of Survival and Regression Under Dependent Truncation and Independent Censoring

Description

This is function computes the perturbed version of the conditional Kendall's tau.

Usage

wKendall(trun, obs, delta = NULL, weights = NULL)

Arguments

trun	left truncation time satisfying trun <= obs.
obs	observed failure time, must be the same length as trun, might be right-censored.
delta	an optional 0-1 vector of censoring indicator (0 = censored, 1 = event) for obs. If this vector is not specified, cKendall assumes no censoring and all observed failure time denote events.
weights	an optional perturbation weights.

Examples

data(channing, package = "boot")
chan <- subset(channing, sex == "Male" & entry < exit)
## When weights is not specified, this function reduces to condKendall()
with(chan, wKendall(entry, exit, cens))
mean(replicate(1000, with(chan, wKendall(entry, exit, cens, rexp(nrow(chan))))))

Example output

[1] 0.1966783
[1] 0.1911418

tranSurv documentation built on Jan. 16, 2021, 5:31 p.m.