Simulating Survival Data Using the <b>simsurv</b> <i>R</i> Package
Samuel L. Brilleman, Rory Wolfe, Margarita Moreno‐Betancur, Michael J. Crowther
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.