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I'd like to have a method to transform R2 indices into multiple correlations (R).
I am thinking a an S3 method for sqrt() that transforms appropriate columns might be good.
sqrt()
m <- lm(mpg ~ disp * hp, data = mtcars) p <- performance::performance(p) sqrt.performance_model <- function(x) { x |> mutate(R2 = sqrt(R2), R2_adjusted = sqrt(R2_adjusted)) |> rename(R = R2, R_adjusted = R2_adjusted) } sqrt(p)
What do you think @strengejacke @mattansb @DominiqueMakowski ? This could also be applied in effectsize.
The text was updated successfully, but these errors were encountered:
This can be added as a column always / show up in the print method, maybe?
Similar to how tolerance shows up in the VIF print.
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This can be added as a column always / show up in the print method
I'm not sure it's necessary to clutter the printing with this as it's not a critical info is it? So I'd say a method sounds good
In most cases, I would expect a user to want one or the other
Does sqrt.performance_model() makes sense, if it only applies to R2? Why not sqrt.r2_class()?
sqrt.performance_model()
sqrt.r2_class()
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I'd like to have a method to transform R2 indices into multiple correlations (R).
I am thinking a an S3 method for
sqrt()
that transforms appropriate columns might be good.What do you think @strengejacke @mattansb @DominiqueMakowski ? This could also be applied in effectsize.
The text was updated successfully, but these errors were encountered: