transform_es {metaBMA} | R Documentation |
Transformation of Effect Sizes
Description
Converts between different measures of effect size (i.e., Cohen's d, log odds ratio, Pearson correlation r, and Fisher's z).
Usage
transform_es(y, SE, from, to)
Arguments
y |
estimate of the effect size (can be vectorized). |
SE |
optional: standard error of the effect-size estimate. Must have the
same length as |
from |
type of effect-size measure provided by the argument |
to |
which type of effect size should be returned (see |
Details
The following chain of transformations is adopted from Borenstein et al. (2009):
logOR <--> d <--> r <--> z
.
The conversion from "d"
to "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).
Value
If SE
is missing, a vector of transformed effect sizes. Otherwise,
a matrix with two columns including effect sizes and standard errors.
References
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
See Also
Examples
# transform a single value of Cohen's
transform_es(y = 0.50, SE = 0.20, from = "d", to = "logOR")
# towels data set:
transform_es(y = towels$logOR, SE = towels$SE, from = "logOR", to = "d")