Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Samuel L. Brilleman, Rory Wolfe, Margarita Moreno-Betancur, Michael J. Crowther
Title: Simulating Survival Data Using the simsurv R Package
Abstract: The simsurv R package allows users to simulate survival (i.e., time-to-event) data from standard parametric distributions (exponential, Weibull, and Gompertz), two-component mixture distributions, or a user-defined hazard function. Baseline covariates can be included under a proportional hazards assumption. Clustered event times, for example individuals within a family, are also easily accommodated. Time-dependent effects (i.e., nonproportional hazards) can be included by interacting covariates with linear time or a user-defined function of time. Under a user-defined hazard function, event times can be generated for a variety of complex models such as flexible (spline-based) baseline hazards, models with time-varying covariates, or joint longitudinal-survival models.

Page views:: 3610. Submitted: 2018-06-05. Published: 2021-01-14.
Paper: Simulating Survival Data Using the simsurv R Package     Download PDF (Downloads: 1506)
Supplements:
simsurv_1.0.0.tar.gz: R source package Download (Downloads: 113; 108KB)
v97i03.R: R replication code Download (Downloads: 124; 12KB)
DOI: 10.18637/jss.v097.i03

by
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.