Regarding meta-analysis, I am wondering whether there is a potential bias due to the ceiling effects (or floor effects) when weighting effect sizes by their sampling error variances.
In case of using standardized mean differences or raw mean scores as effect sizes, we use sampling error variances (by calculating from reported SDs and participant numbers) to weight each effect size. However, SDs tend to become quite small when ceiling effects are observed. I started wondering if just weighting effect sizes by its sampling variances blindly can potentially lead to some kinds of biases for meta-analysis.
Should we care about this? Or, this usually does not bother meta-analysis?
I would appreciate it if you would introduce some articles discussing this issue to me if there is any. Also, I would like to hear ideas on how to deal with this. Just weighting by the number of participants? Or, is there a fancier way to deal with this?