Open
Description
See https://rdrr.io/cran/psych/man/r.test.html
Would be nice to have an easystats version of this.
Here are some mockups:
Independent correlations
Interface 1: pass a grouped data frames
mtcars |>
dplyr::group_by(am) |>
compare_correlations(select = c("mpg", "hp", "drat"))
#> # Differences between independant Pearson correlations
#>
#> Group | Parameter1 | Parameter2 | r1 | r2 | diff | 95% CI | z | p
#> -------------------------------------------------------------------------------------------
#> 0 - 1 | mpg | hp | -0.83 | -0.13 | -0.71 | [-0.93, -0.61] | -6.17 | < .001***
#> 0 - 1 | mpg | drat | 0.47 | 0.50 | -0.03 | [ 0.02, 0.76] | 2.19 | 0.086
#> 0 - 1 | hp | drat | -0.34 | -0.01 | -0.34 | [-0.69, 0.13] | -1.50 | 0.151
#>
Interface 2: name variables
compare_correlations(mtcars, select = c("mpg", "hp", "drat"), group = "am")
Dependent correlations
Not sure...
Effect size
Differences between correlations are already pretty standardized... but there is also the difference between Fished z-transformed correlations, which is called Cohen's q.