Converts between different measures of effect size (i.e., Cohen's d, log odds ratio, Pearson correlation r, and Fisher's z).
transform_es(y, SE, from, to)
estimate of the effect size (can be vectorized).
optional: standard error of the effect-size estimate. Must have the
same length as
type of effect-size measure provided by the argument
which type of effect size should be returned (see
The following chain of transformations is adopted from Borenstein et al. (2009):
logOR <--> d <--> r <--> z.
The conversion from
"r" assumes equal sample sizes per condition (n1=n2).
Note that in in a Bayesian meta-analysis, the prior distributions need to be adapted to the type of effect size. The function
meta_default provides modified default prior distributions for different effect size measures which are approximately transformation-invariant (but results may still differ depending on which type of effect size is used for analysis).
SE is missing, a vector of transformed effect sizes. Otherwise,
a matrix with two columns including effect sizes and standard errors.
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Converting among effect sizes. In Introduction to Meta-Analysis (pp. 45–49). John Wiley & Sons, Ltd. doi: 10.1002/9780470743386.ch7
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