Simulating Survival Data Using the simsurv R Package
Dublin Core
Title
Simulating Survival Data Using the simsurv R Package
Subject
survival, time-to-event, simulation, R
Description
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.
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.
Creator
Samuel L. Brilleman
Source
https://www.jstatsoft.org/article/view/v097i03
Publisher
Samuel L. Brilleman
Monash University
Monash University
Date
Januari 2021
Contributor
Fajar Bagus W
Format
PDF
Language
Inggris
Type
Text
Files
Collection
Citation
Samuel L. Brilleman, “Simulating Survival Data Using the simsurv R Package,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8178.