# Using moderator in metafor Binomial-Normal model that varies within study

I had some data where I had previously examined the proportion with recurrent hepatocellular carcinoma (HCC) using the BN model as such

res<-rma.glmm(measure="PLO",xi=ai1,ni=ni1,data=metadata)
res1p<-predict(res,transf=transf.ilogit,digits=2)


The investigator is now interested in, for example, the effect of gender on HCC recurrence. I have the number of males in each study.

Can this be analyzed?

I ask because in every example I've seen, the mods variable(s) is/are something that only varies between studies (i.e. study year, study location, whatever), not within studies.

Is it possible I could make a study-specific variable to reflect gender, something like proportion male? Or is this not something that can be done?

I'm new to meta-analysis so any help is appreciated.

res2<-rma.glmm(measure="PLO",xi=ai1,ni=ni1,mods=????,data=metadata)


• I am not 100% sure if I understand the analysis you want to do, but it does sound to me like you either need to use rma.mv() for a multilevel model or, if you want to stick to a binomial-normal model, you will have to use glmer() (from the lme4 package) directly. – Wolfgang Mar 27 '17 at 22:30