Multiple Inference documentation#

A statistics package for comparing multiple parameters (e.g., multiple treatments, policies, or subgroups).

Documentation Status


Multiple inference techniques outperform standard methods like OLS and IV estimation for comparing multiple parameters. For example, this post shows how to apply Bayesian estimators to a randomized control trial testing many interventions to increase vaccination rates.

Start here#

Click the badges below to launch a Jupyter Binder with a ready-to-use virtual environment and template code.

This binder is an 80-20 solution for multiple inference.
This binder is for inference after ranking.


Install the latest stable build.

$ pip install conditional-inference

Install the latest dev build.

$ pip install git+


Please submit issues here.


Indices and tables#


   title={ Multiple Inference },
   author={ Bowen, Dillon },
   year={ 2022 },
   url={ }


I would like to thank Isaiah Andrews, Toru Kitagawa, Adam McCloskey, and Jeff Rowley for invaluable feedback on my early drafts.

My issue templates are based on the statsmodels issue templates.