**If** I understand correctly, this is because of correlation in effects due to non-independence between males and females in the data. As this is primarily a statistical, not an R programming, issue, I suggest you post on a statistics list like stats.stackexchange.com. Better yet, talk with a local statistical resource.
If I misunderstand, correction would be appreciated. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Sat, Dec 12, 2015 at 7:35 AM, Carlijn . <wibbelt...@hotmail.com> wrote: > > > Hi all, > > > > I have a question about doing a meta-analysis, in particular a three-level > meta-analysis using Metafor. > > I have estimated the mean overall effect size of males by using two different > ways: > > 1. moderator analysis (male = 0, female = 1) using the whole data set > > 2. intercept-only model with a subset of the data (only males) > > > > The mean effect size estimated by using the categorical moderator analysis > (1) differs considerably from the overall mean effect size estimated in an > intercept-only model using a subset of the data (2). > > > > Can someone explain this? Which method gives a better estimation of the > effect? > > > > Thank you in advance! > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
