Skip to main content

Population Matching

Project description

PyBalance

The pybalance library implements several routines for optimizing the balance between non-random populations. In observational studies, this matching process is a key step towards minimizing the potential effects of confounding covariates. The official documentation is hosted here. An application of this library to matchng in the pharmaceutical setting is presented here: here.

Features

  • Implements linear and non-linear optimization approaches for matching.
  • Utilizes integer program solvers and evolutionary solvers for optimization.
  • Includes implementation of propensity score matching for comparison.
  • Offers a variety of balance calculators and matchers.
  • Provides visualization tools for analysis.
  • Supports simulation of datasets for testing and demonstration purposes.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pybalance-0.1.8.tar.gz (8.6 MB view hashes)

Uploaded Source

Built Distribution

pybalance-0.1.8-py3-none-any.whl (8.6 MB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page