Multiple Inference documentation#

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

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Motivation#

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.

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This binder is for inference after ranking.
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Installation#

Install the latest stable build.

$ pip install conditional-inference

Install the latest dev build.

$ pip install git+https://gitlab.com/dsbowen/conditional-inference.git

Issues#

Please submit issues here.

Contents#

Indices and tables#

Citations#

@software(multiple-inference,
   title={ Multiple Inference },
   author={ Bowen, Dillon },
   year={ 2022 },
   url={ https://dsbowen-conditional-inference.readthedocs.io/en/latest/?badge=latest }
)

Acknowledgements#

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.