I am looking at the possibilities and limitations of meta-meta-analysis (MMA), put differently, pooling the results of multiple meta-analysis. I realise that it is better to include primary studies, but that is not my point here, I'm trying to find out what happens if you do a MMA.
My current issue is about calculating heterogeneity in the MMA. By doing a few tests, I realised that the I2 of the MMA would be different depending on in what way the studies are combined in the MAs. So, example, if we have two MAs that included A, B and C for MA1, and D, E, and F for MA2, the I2 of the MMA can be (very) different, compared to when MA1 included studies A, C, E, and MA2 included B, D, F. I'm not surprised by this, but it made me wonder how this happens and what influences the result. Is the I2 of the MMA even an interpretable number or doesn't it say anything about the results? I assume that the I2 is worth something if there is no heterogeneity in each of the primary MAs. Correct?
Are there any other assumptions that we (must) make and check when doing a MMA? Does anybody have any recommendations for literature on this topic?
If it is relevant, I'm looking at it from an epidemiological point-of-view.