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I knew the linked-in-the-article https://lindeloev.github.io/tests-as-linear/ which is also great. A bit meta on the widespread use of linear models: "Transcending General Linear Reality" by Andrew Abbott, DOI:10.2307/202114

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I read this article when I was in grad school 5 years ago. Absolutely love it and talk about it to this day.

It really makes me frustrated about the ways I was introduced to statistics: brute force memorization of seeming arbitrary formulas.

Here is the Python port of test-as-linear developed by George Ho (eigenfoo): https://github.com/minireference/tests-as-linear/blob/bugfix...

I'm linking to my fork of it because I've added some fixes and filled in some of the missing parts (e.g. Welch's t-test).

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