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


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.


People do do what you suggest and include as a moderator something like proportion of women, average age, and so on. The drawback with doing this is that what the moderator tells you is the effect of being enrolled in a study with a high proportion of women, or a high average age, not the effect of being a woman or an older person. If you are happy with that interpretation for your scientific question then go ahead but many people find it less appealing.

  • $\begingroup$ Ideally, one would want the proportion with HCC for males and females separately and then include a dummy variable to indicate whether the proportion corresponds to a sample of males or females. In the absence of this information, including the proportion of males as a predictor is a possibility, with exactly the caveat mentioned by @mdewey (this is indeed often done, but the limitation of this approach is also often not properly acknowledged). $\endgroup$ – Wolfgang Mar 26 '17 at 13:35
  • $\begingroup$ Thank you, and thanks for the metafor package Wolfgang. Is there a way to adjust for differing tau-squared in rma.glmm? I saw there is no random statement, i.e. I cannot do random=~trt | Study. We may not actually do the regression I mentioned because we don't have enough studies but I'm just curious. $\endgroup$ – Scott Jackson Mar 26 '17 at 17:07
  • $\begingroup$ Also is there any issue with considering two treatment groups from the same meta-analysis as two "independent" studies? i.e. I have 10 studies that had a treatment and a control group, reporting HCC recurrence in each. Can I consider these two groups as separate studies when comparing to my treatment of interest (antiviral)? So the data would have 26 rows, 6 for antiviral, 10 for interferon, 10 for control but interferon and control were assessed in the same ten studies together (but on separate populations of course). $\endgroup$ – Scott Jackson Mar 26 '17 at 17:13
  • $\begingroup$ I think @wolfgang is best placed to answer this but my feeling is you may need to a more multi-level approch using rma.mv $\endgroup$ – mdewey Mar 26 '17 at 19:32
  • $\begingroup$ 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. $\endgroup$ – Wolfgang Mar 27 '17 at 22:30

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