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...ve multiple experiments measuring T1 and T2. Some have one of each. Some only have T1 or T2. Now, in metafor, I've been using rma(yi = logRatio, vi=varLogRatio, mods=~ Drug.Type, data=mydata) This works fine. Out of curiosity, I ran a quickie model in lme4 lmer(logRatio ~ Drug.Type + (1+studyID), data=mydata, weights=varLogRatio) and I noticed that the results are quite different, and this appears due to some variation due to study (after inspecting ranef - note, I included Drug.Type as a fixed effect as there were only two levels). So, I went back to metafor and ran rma(yi = logRatio,...

...model, with no nesting. I have attempted to simplify the call as much as possible (by creating another grouped object, instead of using subset= and compacting the fixed and random expressions.) This is a what the grouped data object looks like: levelI.data[1:2,] Grouped Data: GMAE ~ AGE | STUDYID STUDYID TIME SCORE INCURVES MOST FIRST AGE 19 1005 1 ACTUAL (unaided) in JAMA curves Level I Level I 49.11301 20 1005 2 ACTUAL (unaided) in JAMA curves Level I Level I 56.53745 GMFM GMFCS GMAE YRS 19 91.03394 1 74.16 4.0927...