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# effectsize: computing effect sizes in Python
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[![PyPI version](https://badge.fury.io/py/effectsize.svg)][pypi]
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[![GitHub](https://img.shields.io/github/license/nbashir97/effectsize)][license]
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[![PyPI](https://badge.fury.io/py/effectsize.svg)][pypi]
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[![License](https://img.shields.io/github/license/nbashir97/effectsize)][license]
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`effectsize` is a comprehensive Python package for computing effect sizes (ESs), also known as standardized differences. The package implements the methodology outlined by [Yang and Dalton, 2012][yang2012] and it provides complex functionality, such as the ability to deal with skewed variables, multinomial categories, and weighted statistics.
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## License
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[MIT License][mit]
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[MIT License][license]
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[pypi]: https://pypi.org/project/effectsize/
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[license]: https://github.com/nbashir97/effectsize/blob/main/LICENSE.md
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[nhanes]: https://www.cdc.gov/nchs/nhanes/index.htm
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[pulling]: https://help.github.com/en/github/collaborating-with-issues-and-pull-requests/creating-a-pull-request
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[forking]: https://docs.github.com/en/get-started/quickstart/fork-a-repo
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[mit]: https://opensource.org/licenses/MIT

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