[R-meta] order of effect sizes in data file changes results
Van Meter, Anna
@v@nmeter @ending from northwell@edu
Sun Dec 30 04:42:32 CET 2018
As described in a previous post, I am conducting a meta analysis of bipolar disorder prevalence rates. Some studies report multiple prevalence rates; for example, one study could report the prevalence for bipolar I and for the full bipolar spectrum, which would include people with bipolar I, plus other people who have other subtypes of bipolar disorder. There are three potential prevalence categories: bipolar I, bipolar I & II, all bipolar.
I am using the Berkey approach to account for the overlap in effect sizes and, based on a helpful response, have set the model up as follows to estimate the average prevalence for each subtype (threegroup is a dummycode for the subtype, articleno is the study ID):
resmvberkeyhybrid<-rma.mv(yi, berkeyV, mods = ~ threegroup, random = ~ threegroup | articleno, struct="UN", method="ML",data=kidtall1, digits=4)
I have noticed that the results of the model change depending on how the .csv data file is ordered, why would the order of the data file matter? And, what is the correct way to order the data file? My guess would be first by articleno and then by threegroup.
Thank you for your help!
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