A pure-julia take on standard survival analysis modeling.
The SurivalModels.jl package is part of the JuliaSurv survival analysis suite. It provides the necessary tools to perform modeling of survival data, from non-parametric estimators and tests to semi-parametric and fully-parametric models.
The package available on Julai's General registry, therefore you can use the following to install it :
] add SurvivalModelsThe package targets for the moment the following features:
- Nonparametric
- Kaplan-Meier
- Log-rank test (including stratification)
- Semi-parametric
- Cox (See PR #15)
- Aalen
- Parametric
- General Hazard models
- Frailties ?
- Mixed models ?
- More generic predictors such as splines ?
- Junction with
NetSurvival.jlto provide the same models on net survival instead of survival ? (i.e. with a population mortality offset.) - [ ]
- Something else on this list ? Open a PR :)
In term of interface, we leverage the standard modeling interface from StatsBase.jl/StatsAPI.jl/StatsModels.jl.
Some of the models might not provide all the outputs you need for the moment. Feel free to open an issue to tell us, we'll look at it and add the features if we can :)
If you want to contribute to the package, ask a question, found a bug or simply want to chat, do not hesitate to open an issue on this repo. General guidelines on collaborative practices (colprac) are available at https://github.com/SciML/ColPrac.