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BiomedSciAI / causallib

A Python package for modular causal inference analysis and model evaluations
Apache License 2.0
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Causal survival models #25

Closed liorness closed 2 years ago

liorness commented 2 years ago

Adding models for estimating counterfactual outcomes in a setting of right-censored data (also known as survival analysis, or time-to-event modeling).

The methods that are currently available are:

  1. Weighting: causallib.survival.WeightedSurvival - uses causallib's WeightEstimator (e.g., IPW) to generate weighted pseudo-population for survival analysis.
  2. Standardization (parametric g-formula): causallib.survival.StandardizedSurvival - fits a parametric hazards model that includes baseline covariates. Can use a scikit-learn classifier for pooled regression or a lifelines fitter.
  3. Weighted Standardization: causallib.survival.WeightedStandardizedSurvival - combines the two above-mentioned methods.
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