# simSurv: The function that simulates independent/cluster-correlated... In SemiCompRisks: Hierarchical Models for Parametric and Semi-Parametric Analyses of Semi-Competing Risks Data

## Description

The function to simulate independent/cluster-correlated right-censored survival data under Weibull/Weibull-Normal model.

## Usage

 1 simSurv(id=NULL, x, beta.true, alpha.true, kappa.true, sigmaV.true=NULL, cens) 

## Arguments

 id a vector of cluster information for n subjects. The cluster membership must be set to consecutive positive integers, 1:J. Required only when generating clustered data. x covariate matrix, n observations by p variables. beta.true true value for β. alpha.true true value for α. kappa.true true value for κ. sigmaV.true true value for σ_V. Required only when generating clustered data. cens a vector with two numeric elements. The right censoring times are generated from Uniform(cens[1], cens[2]).

## Value

simSurv returns a data.frame containing univariate time-to-event outcomes from n subjects. It is of dimension n\times 2: the columns correspond to y, δ.

 y a vector of n times to the event delta a vector of n censoring indicators for the event time (1=event occurred, 0=censored)

## Author(s)

Kyu Ha Lee and Sebastien Haneuse
Maintainer: Kyu Ha Lee <[email protected]>

## Examples

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22  set.seed(123456) J = 110 nj = 50 n = J * nj id <- rep(1:J, each = nj) x = matrix(0, n, 2) x[,1] = rnorm(n, 0, 2) x[,2] = sample(c(0, 1), n, replace = TRUE) beta.true = c(0.5, 0.5) alpha.true = 1.5 kappa.true = 0.02 sigmaV.true = 0.1 cens <- c(30, 40) simData <- simSurv(id, x, beta.true, alpha.true, kappa.true, sigmaV.true, cens) 

SemiCompRisks documentation built on May 7, 2018, 9:04 a.m.