Anyone using open-source tooling to simulate group sequential or Bayesian adaptive designs in rare disease RCTs? I need to model 60–80 participants with 2:1 allocation and a time-to-event endpoint with potential delayed effects, and I’m after packages or workflows with clear vignettes and code for estimating operating characteristics across varying accrual and dropout.
For your 60–80, use simtrial + gsDesign2; simtrial handles accrual, dropout, 2:1, and ‘delayed effects’ — see CRAN: Package simtrial.
And if you want a one-stop R workflow, rpact::getSimulationSurvival covers your 60–80 with 2:1, accrual/dropout, and ‘delayed effects’ via piecewise hazards, with clear vignettes: CRAN: Package rpact. Bayesian isn’t native there; if you truly need Bayesian stopping, simulate in simtrial and fit a piecewise-exponential in brms for posterior-predictive OCs, otherwise GSD should be enough.
Prototype 60–80 time-to-event in simsurv + targets for ‘delayed effects’ and 2:1 (CRAN: Package simsurv); specify hazards carefully, @jacwils.
Quick tip: for your ‘60–80’ with 2:1 and a TTE endpoint, I’ve had good luck using flexsurv::rpexp to impose late separation via a piecewise hazard and then fanning out entry-rate/attrition scenarios in parallel with furrr to stabilize OC estimates; see CRAN: Package flexsurv. Small caveat: if you’re layering a Bayesian rule, do a prior predictive calibration first because even weak priors can bite at this size — want a minimal template?