Causal Inference for Python
Project description
CausalInference
CausalInference is a Python implementation of statistical and econometric methods in the field variously known as Causal Inference, Program Evaluation, and Treatment Effect Analysis.
Work on CausalInference started in 2014 by Laurence Wong as a personal side project. It is distributed under the 3-Clause BSD license.
The most current development version is hosted on GitHub at: https://github.com/laurencium/causalinference
Main Features
Estimation of propensity score
Assessment of overlap in covariate distributions
Improvement of covariate balance through trimming
Subclassification on propensity score
Estimation of treatment effects via matching, blocking, weighting, and least squares
Dependencies
NumPy: 1.8.2 or higher
SciPy: 0.13.3 or higher
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