[R-meta] mean-variance relationships introduces additional heterogeneity, how?
I thought the existence of outlying effect estimates under SMD and lack of it under LRR could attest to the existence of heterogeneity-generating artefacts like mean-sd relationships (and/or variation in measurement error) across the studies. If not, then, would you mind commenting on why a more symmetric and well-behaved effect distribution is equated with its appropriateness for a set of summaries (e.g., means & sds) from studies? Luke
On Mon, Oct 25, 2021 at 8:47 PM James Pustejovsky <jepusto at gmail.com> wrote:
Responses below. On Mon, Oct 25, 2021 at 4:21 PM Luke Martinez <martinezlukerm at gmail.com> wrote:
Sure, thanks. Along the same lines, if I see that the unconditional distribution of the SMD estimates is multi-modal or right or left skewed (perhaps due to extreme outliers), but the unconditional distribution of the corresponding LRR estimates looks more symmetric and well-behaved, does that also empirically suggest a mean-sd relationship in one or more groups?
I'm not sure that it implies a mean-sd relationship. But I think it does suggest that LRR might be a more appropriate metric.
PS. Is there a reason for exploring the mean-sd relationship specifically in the control group?
No, you could certainly examine the relationships in the treatment group(s) as well.