Converts correlation (r) to an effect size of $d$ (mean difference), $g$ (unbiased estimate of $d$), $r$ (correlation coefficient), $z'$ (Fisher's $z$), and log odds ratio. The variances of these estimates are also computed.
Usage
res(r, var.r = NULL, n)
Arguments
r
Correlation coefficient.
var.r
Variance of r. If value is not reported then leave it blank and variances will be computed based on sample size. Otherwise, enter this value (e.g., r_to_es(.27, var.r = .02, 30).
n
Total sample size.
Value
dStandardized mean difference ($d$).
var.dVariance of $d$.
gUnbiased estimate of $d$.
var.gVariance of $g$.
rCorrelation coefficient.
var.rVariance of $r$.
log.oddsLog odds ratio.
var.log.oddsVariance of log odds ratio.
nTotal sample size.
References
Borenstein (2009). Effect sizes for continuous data. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta analysis (pp. 279-293). New York: Russell Sage Foundation.