diff_to_cles | R Documentation |
Convert Standardized Differences to Common Language Effect Sizes
d_to_p_superiority(d) rb_to_p_superiority(rb) rb_to_vda(rb) d_to_u2(d) d_to_u1(d) d_to_u3(d) d_to_overlap(d) rb_to_wmw_odds(rb)
d, rb |
A numeric vector of Cohen's d / rank-biserial correlation or
the output from |
This function use the following formulae for Cohen's d:
Pr(superiority) = pnorm(d / sqrt(2))
U3 = pnorm(d)
U2 = pnorm(abs(d)/2)
U1 = (2 * U2 - 1) / U2
Overlap = 2 * pnorm(-abs(d) / 2)
And the following for the rank-biserial correlation:
Pr(superiority) = (rb + 1)/2
WMW_{Odds} = Pr(superiority) / (1 - Pr(superiority))
A list of Cohen's U3
, Overlap
, Pr(superiority)
, a
numeric vector of Pr(superiority)
, or a data frame, depending
on the input.
For d, these calculations assume that the populations have equal variance and are normally distributed.
Vargha and Delaney's A is an alias for the non-parametric probability of superiority.
Cohen, J. (1977). Statistical power analysis for the behavioral sciences. New York: Routledge.
Reiser, B., & Faraggi, D. (1999). Confidence intervals for the overlapping coefficient: the normal equal variance case. Journal of the Royal Statistical Society, 48(3), 413-418.
Ruscio, J. (2008). A probability-based measure of effect size: robustness to base rates and other factors. Psychological methods, 13(1), 19–30.
cohens_u3()
for descriptions of the effect sizes (also,
cohens_d()
, rank_biserial()
).
Other convert between effect sizes:
d_to_r()
,
eta2_to_f2()
,
odds_to_probs()
,
oddsratio_to_riskratio()
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