Flexible parametric survival models
Everything Red Door Analytics has published on flexible parametric survival models — the packages that fit it, the tools that show it, the tutorials that work it through, and where it decided something.
A fully parametric survival model whose baseline is a spline rather than a single shape, so the hazard is free to rise and fall. It gives smooth predictions, extrapolates deliberately, and is estimable where a Cox model is not.
Also called royston-parmar, spline-based survival.
A narrower method under survival analysis.
Learn it1
Flexible parametric survival analysisTaught live by the team, online, two to three times a year.
Fit it2
Try it now2
Reconstruct & extrapolate a KM curve Build a merlin modelRuns in your browser. Nothing installed, nothing uploaded.
Worked through1
The evidence10
- Bayesian pairwise meta-analysis of time-to-event outcomes in the presence of non-proportional hazards: A simulation study of flexible parametric, piecewise exponential and fractional polynomial models.
- A flexible parametric accelerated failure time model and the extension to time-dependent acceleration factors.
- On the choice of timescale for other cause mortality in a competing risk setting using flexible parametric survival models.
- Modelling multiple time-scales with flexible parametric survival models.
- Flexible parametric survival analysis with multiple timescales: Estimation and implementation using stmt.
- Capturing simple and complex time-dependent effects using flexible parametric survival models: A simulation study.