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Python package for targeted inference.

Project description

Targeted Learning Library

Python package for targeted inference.

targeted provides a number of methods for semi-parametric estimation. The library also contains implementations of various parametric models (including different discrete choice models) and model diagnostics tools.

The implemention currently includes

  • Risk regression models with binary exposure (Richardson et al., 2017, doi:10.1080/01621459.2016.1192546)
  • Augmented Inverse Probability Weighted estimators for missing data and causal inference (Bang and Robins, 2005, doi:10.1111/j.1541-0420.2005.00377.x)
  • Model diagnostics based on cumulative residuals methods
  • Efficient weighted Pooled Adjacent Violator Algorithms
  • Nested multinomial logit models

Documentation and tutorials can be found at

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