bigtcr (version 1.1)

get.gap.ccif: Conditional Bivariate Cumulative Incidence Function Estimation

Description

Estimate the conditional bivariate cumulative incidence function. See bigtcr-package.

Usage

get.gap.ccif(obs.y, event, v, tau = Inf)

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

Value

A matrix with class gap.ccif that has \(J+2\) columns. Column 1 and 2 are \((v,w)\). The rest columns correspond to \(H_1(v,w)\) to \(H_J(v,w)\). Each row represents a distinct observed time point and the row name contains the value of this time point.

Examples

# NOT RUN {
Hj <- get.gap.ccif(obs.y=pancancer$obs.y, event=pancancer$min.type, v=pancancer$v, tau=120)

# }