bigtcr (version 1.1)

get.gap.pval: Comparison of Bivariate CCIF

Description

Compare the bivariate CCIF of different failure typess by applying the technique of permutation test. See bigtcr-package.

Usage

get.gap.pval(obs.y, event, v, tau = Inf, comp.event = c(1, 2), np = 1000,
  Kt = function(x) {     1 })

Arguments

obs.y

\(Y\): time to failure events or censoring

event

0: censored; \(1, \ldots J\): type of failure events

v

Time to the first failure event (e.g. disease recurrence)

tau

Conditioning time \(\tau\) under which the CCIF is defined

comp.event

Failure events for CCIF comparison

np

Number of permutations

Kt

A weight function that takes one parameter \(t\) and return the weight for \(t\). Default weight function is constant \(1\)

Value

P-value of the hypothesis test \(H_0: H_j = H_k = \ldots = H_l\).

Examples

# NOT RUN {
gap.pval <- get.gap.pval(pancancer$obs.y, pancancer$min.type, pancancer$v,
                         tau=120, comp.event=c(1,2), np=20);

# }