pycausalgps

Causal Inference with Generalized Propensity Score

pycausalgps is a Python library for implementing matching on generalized propensity scores (GPS) with continuous exposures. We have developed an innovative approach for estimating causal effects using observational data in settings with continuous exposures and introduced a new framework for GPS caliper matching that jointly matches on both the estimated GPS and exposure levels to fully adjust for confounding bias.

Introduction

• About

Researchers

• Setting Up Environment
  • Conda
• Quickstart
  • Installing the Package
  • Generating Synthetic Data
  • Estimating GPS values
  • Generating Pseudo-population
  • Exposure Response Function
• Frequently Asked Questions

Developers

• Development Environment
  • Setting up a new environment
  • Updating an existing environment
  • Installing pycausalgps
  • Registering the kernel
  • Updating the environment recipe
• Documentation
• Git Branching Model
• Modules

Community

• Contact Us
• Changelog
  • pycausalgps 0.0.3 - 2022-06-07

Indices and tables

• Index

• Module Index

• Search Page