Metadata-Version: 2.4
Name: inferential-analysis
Version: 1.0.1
Summary: Pure-Python inferential analysis
License-Expression: Apache-2.0
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Typing :: Typed
Requires-Python: >=3.14
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: marginaleffects>=0.5.0
Requires-Dist: numpy>=2.4.4
Requires-Dist: pandas>=3.0.2
Requires-Dist: plotnine>=0.15.4
Requires-Dist: scipy>=1.17.1
Requires-Dist: statsmodels>=0.14.4
Dynamic: license-file

# Inferential Analysis

The book _"Validity, Reliability, and Significance: Empirical Methods for NLP and Data Science"_, written by Stefan Riezler and Michael Hagmann,
uses the `inferential analysis` module found at https://github.com/StatNLP/empirical_methods to conduct inferential reproducibility analyses.

The aim of this project is to offer functionality similar to that of the original `inferential_analysis` module, but without depending on `R` and `lme4`.

## Installation

The library can be found on PyPI.

```sh
# pip
pip install inferential-analysis

# uv
uv add inferential-analysis
```

## Usage Examples

The usage examples are based on [this Jupyter notebook](https://github.com/StatNLP/empirical_methods/blob/ddcaccd35850f9097cbe4327c8e99a3dd507acb9/inferential_reproducibility/example-large_language_model.ipynb) and can be found in the `examples` directory of the [repository](https://github.com/lkarp-744/inferential-analysis/tree/main).

## Additional Information

- Changes are tracked in the [Changelog](https://github.com/lkarp-744/inferential-analysis/blob/9b82e17965b40e28bf9d79cf265d7346fc4296b5/CHANGELOG.md)

## License

In accordance with the original implementation this library is licensed under the [Apache 2.0 license](https://github.com/lkarp-744/inferential-analysis/blob/9b82e17965b40e28bf9d79cf265d7346fc4296b5/LICENSE).
