Example Gallery #558
Example Gallery #558
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That is nice. Can only look on my phone now, will review tomorrow. |
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| ## ANCOVA | ||
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| Analysis of covariance is a simple linear model, typically with one continuous predictor (the covariate) and a categorical variable (which may correspond to treatment or control group). In the context of this package, ANCOVA could be useful in pre-post treatment designs, either with or without random assignment. This is similar to the approach of difference in differences, but only applicable with a single pre and post treatment measure. |
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@drbenvincent feel free to push edits to these descriptions :)
juanitorduz
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juanitorduz
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On model descriptions :)
drbenvincent
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drbenvincent
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Thanks for doing this. Here's quick, first-pass review.
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The left nabber feels rather empty now. It is possible to kill that? Or move the navigation (on the right) to the left and kill the right nav bar?
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I notice the menu is now "Example Gallery" rather than "How-to". Don't know if I have strong feelings either way, but it's worth seeing if a consensus favourite emerges. If we switch I guess we should grep for any mentions of "how-to".
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Can you give a thorough enough description in
CONTRIBUTING.mdandAGENTS.mdso that it's clear what to do when there's a new notebook.
I'll take a look at, and maybe edit, the descriptions in another round.
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Thanks @drbenvincent ! Regarding your comments: The left nabber feels rather empty now. It is possible to kill that? Or move the navigation (on the right) to the left and kill the right nav bar? -> Added a table of contents on the side. I notice the menu is now "Example Gallery" rather than "How-to". Don't know if I have strong feelings either way, but it's worth seeing if a consensus favourite emerges. If we switch I guess we should grep for any mentions of "how-to". -> Reverted back to how-to for now. Can you give a thorough enough description in CONTRIBUTING.md and AGENTS.md so that it's clear what to do when there's a new notebook. done |
Show the examples in a gallery mode following the approach of pymc-labs/pymc-marketing#1611
📚 Documentation preview 📚: https://causalpy--558.org.readthedocs.build/en/558/