[R-meta] Effect size calculation

Hi Tharaka,

There are formulas in the literature for converting between a
standardized mean difference (of which Hedges' g is an estimate) and
the Pearson correlation, as well as from other test statistics (F, t,
X^2); See Jacobs & Viechtbauer (2017) and Pustejovsky (2014). However,
the formulas are only valid under specific distributional assumptions
about the variables involved (e.g., that a continuous predictor has
been artificially dichotomized, and that interest is in the
correlation between the continuous predictor) and the outcome. For the
study you attached, it's not at all clear why the authors would use
the Pearson correlation coefficient as the effect size measure. If I
understand correctly, they are interested in the effects of
contrasting treatment conditions (AES vs. control) so the assumptions
for converting from SMD to r would not really make sense here.

James

Jacobs, P., & Viechtbauer, W. (2017). Estimation of the biserial
correlation and its sampling variance for use in meta?analysis.
Research synthesis methods, 8(2), 161-180.
Pustejovsky, J. E. (2014). Converting from d to r to z when the design
uses extreme groups, dichotomization, or experimental control.
Psychological methods, 19(1), 92.

On Tue, Dec 21, 2021 at 5:32 AM Tharaka S. Priyadarshana

[R-meta] Effect size calculation

Thread (2 messages)