RDA avalon
Survival-data simulation in R and Stata under one name — standard, flexible parametric, fitted-model and user-defined hazards, with competing risks and multi-state structures. In active development.
Coming
November 2026
Not yet released avalon is in build for R and Stata.
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What avalon does
avalon simulates survival data from a wide range of hazard specifications — standard parametric distributions, flexible parametric (spline) models, fitted models, and fully user-defined hazard or log-hazard functions — with time-dependent effects, competing risks, multi-state structures, and left truncation. It is the workhorse the rest of the family is tested against: the known-truth data generator behind merlin, morgana, and pendragon's validation.
It is a complete rewrite, with a new syntax, of Michael Crowther's survsim package (no longer developed), and brings one simulation engine to both ecosystems under one name, so a project that spans R and Stata no longer needs a different simulation package in each. simsurv (Brilleman et al.) remains the established R option and is unaffected by this.
avalon is in active development.
Simulate almost any survival process — in Stata or R
avalon brings its simulation scope into one cross-ecosystem package. The capabilities below describe that target scope; the package is in active development.
Standard & flexible parametric
Exponential, Weibull, Gompertz, and Royston-Parmar / log-hazard spline baselines — or simulate from a fitted model.
Custom hazards
Simulate from any user-supplied hazard or log-hazard function — no closed form required.
Competing risks & multi-state
Competing-risks and multi-state data, with time-dependent effects and left truncation.
R + Stata parity
The same simulation API and behaviour in R and Stata.
Get started
avalon is in active development in both R and Stata, and is not yet on SSC or CRAN.
avalon is not released yet. Get in touch if you'd like early access.
A first model
avalon is in build. Both blocks show the intended interface.
Planned syntax. The blocks marked planned show the interface being built, not a command you can run today. They may change before release.
library(avalon)
# survival times from a Weibull model with a treatment effect,
# administratively censored at five years
d <- avalon(
n = 1000,
distribution = "weibull",
lambda = 0.1, gamma = 1.2,
covariates = list(trt = 0.5),
maxtime = 5
)* survival times from a Weibull model with a treatment effect,
* administratively censored at five years
avalon stime died, distribution(weibull) lambda(0.1) gamma(1.2) ///
covariates(trt 0.5) maxtime(5)The simulation workhorse
Worked examples and tutorials for the family are in our Resources.
Try it in your browser: the survival DGM explorer and the multi-state explorer — choose a data-generating mechanism interactively, then export run-ready avalon code.
Citing avalon
avalon does not have a methods paper yet — cite the software itself.
@misc{avalon2026,
author = {Crowther, Michael J.},
title = {{avalon: flexible simulation of survival data}},
year = {2026},
url = {https://reddooranalytics.se/software/avalon/},
note = {Red Door Analytics}
}