[R-meta] meta-analysis of response ratios with low sample sizes
Dear Ana Comments in-line
On 18/01/2019 15:24, Ana Benitez wrote:
Dear Wolfgang (and users of the meta-analysis mailing list), I am currently conducting a meta-analisis where I want to assess body size shifts in vertebrates living in islands compared to mainland populations (a.k.a the island rule). I am using response ratios between the mean size of the island population and the mean size of the mainland population. In some cases I have measurements for only 2 specimens, and I calculate mean and SD for those 2 specimens in order to calculate the sampling variance. However, many people would argue that calculating the SD of 2 data points is a bit meaningless in most contexts, but in a meta-analytical context I would expect that response ratios based on N = 2 for either the treatment or control, or both, would be downweighted in the metaanalysis and thus it is both informative and interesting to include them in the analyses. I would like to know if other people have encountered these situations and how they dealt with it. Also, what?s your opinion, Wolfgang?
I think your feeling that (a) you can do it (b) they will be downweighted is correct.
I have a second query, in this same analysis I have cases where only one specimen is measured, and thus the SD is zero. To be able to calculate the sampling variance I add a small constant (0.5) to both the numerator and denominator of the formula. Is this a sensible way to proceed or shall I just discard cases where only 1 specimen is measured in either of the two populations (or both of them)?
I do not like excluding anything but in this case I think it might be better than adding an arbitrary constant. If I was forced to add a constant by powerful figures then I would use a range of values to check whether the specific value I added was crucial. If it is then I would be even more doubtful about the wisdom of adding it. Michael
Thanks a lot for your time, I am looking forward to your thoughts on these two queries. Best, Ana