diff_to_cles {effectsize} | R Documentation |
Convert Standardized Differences to Common Language Effect Sizes
Description
Convert Standardized Differences to Common Language Effect Sizes
Usage
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)
Arguments
d , rb |
A numeric vector of Cohen's d / rank-biserial correlation or
the output from |
Details
This function use the following formulae for Cohen's d:
And the following for the rank-biserial correlation:
Value
A list of Cohen's U3
, Overlap
, Pr(superiority)
, a
numeric vector of Pr(superiority)
, or a data frame, depending
on the input.
Note
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.
References
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.
See Also
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()
,
w_to_fei()