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Weighting is already implemented in standardize.default() and standardize_parameters() (and eta_squared() via the fit models).
standardize.default()
standardize_parameters()
eta_squared()
Would be nice to have this also (with weights = arg) in:
weights =
cohens_d()
cramers_v()
Perhaps we can steal borrow some code from sjstats::weighted_*...
sjstats::weighted_*
The text was updated successfully, but these errors were encountered:
For all the Xsq stuff, this seems easy - essentially, all suppressWarnings(stats::chisq.test(x, y, ...)) should be replaced with:
suppressWarnings(stats::chisq.test(x, y, ...))
chisq.test2 <- function(x, y, w = NULL, ...) { if (!is.null(w)) { x <- stats::xtabs(w ~ x + y, data = mtcars) y <- NULL } suppressWarnings(stats::chisq.test(x, y, ...)) } chisq.test2(mtcars$am, mtcars$cyl) #> #> Pearson's Chi-squared test #> #> data: x and y #> X-squared = 8.7407, df = 2, p-value = 0.01265 chisq.test2(mtcars$am, mtcars$cyl, w = mtcars$gear) #> #> Pearson's Chi-squared test #> #> data: x #> X-squared = 26.383, df = 2, p-value = 1.866e-06
Created on 2021-11-30 by the reprex package (v2.0.1)
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Weighting is already implemented in
standardize.default()
andstandardize_parameters()
(andeta_squared()
via the fit models).Would be nice to have this also (with
weights =
arg) in:cohens_d()
etccramers_v()
etcPerhaps we can
stealborrow some code fromsjstats::weighted_*
...The text was updated successfully, but these errors were encountered: