tvc.example: Creates an example of a matrix of time-varying covariates

In mhazard: Nonparametric and Semiparametric Methods for Multivariate Failure Time Data

Creates an example of a matrix of time-varying covariates

Description

Given a set of (non-time-varying) covariates, creates a simple example of a matrix of time-varying covariates that can be used as input data for the mHR2.tvc function.

Usage

tvc.example(Y1, Y2, Delta1, Delta2, X)

Arguments

Y1, Y2	Vectors of event times (continuous).
Delta1, Delta2	Vectors of censoring indicators (1=event, 0=censored).
X	Matrix of covariates (continuous or binary).

Value

A list containing the following elements:

ids:

A vector of ids

X.tv:

Time-varying covariate matrix

Details

For each (non-time-varying) covariate in X, two time-varying covariates are created. The first time-varying covariate is equal to Xlog(T1), and the second is equal to Xlog(T2). (If T=0, then the time-varying covariate is set to be 0.) A vector of ID numbers and a matrix of time-varying covariates are created in a format that can be passed to the mHR2.tvc function.

See Also

mHR2, genClaytonReg

Examples

x <- genClaytonReg(250, 2, 0.5, 1, 1, 0, log(2), 0, 5, 5)
x.tv <- tvc.example(x$Y1, x$Y2, x$Delta1, x$Delta2, x$X)

mhazard documentation built on Aug. 17, 2023, 5:12 p.m.