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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

Package source and binary distribution files are available from PyPi: https://pypi.python.org/pypi/CausalInference

Main Features

  • Assessment of overlap in covariate distributions

  • Estimation of propensity score

  • 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

Installation

CausalInference can be installed using pip, and will run provided the necessary dependencies are in place.

On Ubuntu systems, the following commands should take care of all the essential steps if you are starting from scratch:

$ sudo apt-get update
$ sudo apt-get install python-pip python-numpy python-scipy
$ sudo pip install causalinference

Project details


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CausalInference-0.0.5.tar.gz (21.9 kB view hashes)

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