Reviewer asked me why I use meta-regression as a way how to deal with heterogeneity among effect sizes instead of conducting stratified meta-analysis.
I tried to google "stratified meta-analysis" and probably the most useful explanation was:
Stratification is an effective way to deal with inherent differences among studies and to improve the quality and usefulness of the conclusions. An added advantage to stratification is that insight can be gained by investigating discrepancies among strata. There are many ways to create coherent subgroups of studies. For example, studies can be stratified according to their “quality,” assigned by certain scoring systems. Commonly used systems award points on the basis of how patients were selected and randomized, the type of blinding, the dropout rate, the outcome measurement, and the type of analysis (eg, intention-to-treat).
Walker, E., Hernandez, A. V., & Kattan, M. W. (2008). Meta-analysis: Its strengths and limitations. Cleveland Clinic Journal of Medicine, 75(6), 431–439.
From what I understand, the I should make some scoring system for my sample of studies, and use that score as a "weight" in my meta-analytic model? I do not like this idea. It seems to my more less objective than meta-regression mainly because I have no criteria in my studies to make the score. (I am doing meta-analysis of ecological studies.)
May I use this as an argument in response that stratified meta-analysis will be less objective in my case?