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ludist avatar ludist commented on September 27, 2024

Looking at the closed issues, I see you very recently addressed this at #906 here for a slightly different issue and I notice there's been a very recent commit. I'll update my package installation and investigate.

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ludist avatar ludist commented on September 27, 2024

Wow, I don't know what changed in the last 72 hours or so but updating statsExpression sent me into an hour and a half dependency hell where I had to manually install a gfortran compiler and 3 other packages on macOS x64 before I could get it working again. If anyone reading this has the same problem, just save yourself the hassle and google the package names and "macOS binaries" to get to the r-project page and then install the .tgz manually.

Anyway, I tried running the code again, along with several attempts at parameter calls based on my review of the commits, and I still get 1.00 for the second CI. If it's fixed and requires a parameter call, could you expand on the documentation a bit? Thanks again!

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IndrajeetPatil avatar IndrajeetPatil commented on September 27, 2024

Yes, this upper bound for the effect size for KW (rank epsilon squared) is 1.0.

For more, see: https://easystats.github.io/effectsize/reference/rank_epsilon_squared.html

Screenshot 2024-03-21 at 18 57 44

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ludist avatar ludist commented on September 27, 2024

Thank you!

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IndrajeetPatil avatar IndrajeetPatil commented on September 27, 2024

The underlying functions used to run inferential statistics and effect size estimation are catalogued here, and more details can be found in linked pages:

https://indrajeetpatil.github.io/ggstatsplot/reference/ggbetweenstats.html#one-way-anova

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