Dear All
I wondered if anyone could help with an issue about aggregating effect sizes? I have 3 effect sizes from one study that come from one sample and so I want to aggregate them into one. The result of escalc is this
Study yi vi
Arnold -0.2386 0.2014
Arnold 0.4556 0.2052
Arnold 0.0563 0.2001
so then I used the agg function from MAd
ag<-agg(id=Study, es=yi, var=vi, cor=.5, method="BHHR", mod=NULL, data=ma)
which gives the following which I think I can then use as one study in my meta-analysis
id es var
1 Arnold 0.09111254 0.1348174
Does this seem reasonable? Also as I don't know the correlation between the three effect sizes I have just used the default of 0.5. I suspect this is low, but that is just a guess - is that reasonable?
Thanks
Emily
[R-meta] Using MAd agg function
2 messages · Emily Russell, AC Del Re
Hi Emily, Technically, yes, you have accounted for dependent effect sizes (ES) and could use this aggregate ES in further analyses. However, I think it depends on the actual outcomes and if it makes sense to aggregate. For example, 3 measures of psychological symptomology would probably make sense to combine (well depending on your research questions) but combining, say measures of intelligence, psychological traits, and physical endurance, might not. Regarding the estimated correlation, there are a few possibilities to consider: (1) check previous literature in your substantive area about the correlation among the outcomes and use that value as the estimate; (2) if there are enough studies providing each of these outcomes, check the correlation between them in your data and use that; (3) conduct sensitivity analyses at a few different correlation values and see if there are any substantial differences. Bill Hoyt and I just published an article examining this issue (and other issues with effect sizes) within psychotherapy studies. You can get it here: www.acdelre.com/pubs Hope this helps, AC
AC Del Re, PhD acdelre.com On Sun, Dec 17, 2017 at 3:20 AM, Emily Russell <emilyrussell99 at outlook.com> wrote: > Dear All > > > I wondered if anyone could help with an issue about aggregating effect > sizes? I have 3 effect sizes from one study that come from one sample and > so I want to aggregate them into one. The result of escalc is this > > > Study yi vi > Arnold -0.2386 0.2014 > Arnold 0.4556 0.2052 > Arnold 0.0563 0.2001 > > > so then I used the agg function from MAd > > > ag<-agg(id=Study, es=yi, var=vi, cor=.5, method="BHHR", mod=NULL, data=ma) > > which gives the following which I think I can then use as one study in my > meta-analysis > > id es var > 1 Arnold 0.09111254 0.1348174 > > Does this seem reasonable? Also as I don't know the correlation between > the three effect sizes I have just used the default of 0.5. I suspect this > is low, but that is just a guess - is that reasonable? > > Thanks > > Emily > > > > [[alternative HTML version deleted]] > > _______________________________________________ > R-sig-meta-analysis mailing list > R-sig-meta-analysis at r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis > [[alternative HTML version deleted]]