I am currently conducting a meta-analysis in which I need to use a mixed treatment comparison method. As I understand it, this method works in the following way:
Say you have a group of studies that make the following set of treatment comparisons:
- Intervention 1
- Intervention 2
- Intervention 3
- Control
You are interested in all possible comparisons between these treatments. So, not only are you interested in intervention 1 versus control, intervention 2 versus control, and intervention 3 versus control, but also intervention 1 versus intervention 2, intervention 1 versus intervention 3, etc. The problem occurs in that not all of the studies in your meta analysis include each intervention type. So, while study 1 may have tested intervention 1, intervention 2, and a control group, study 2 tested intervention 2 and intervention 3 versus a control group. And so on. Mixed treatment comparisons (Caldwell, Ades, & Higgins, 2005; Lu & Ades, 2004; Mills et al., 2011) arose as a way of using the indirect information from your sample of studies to estimate the magnitude of the missing comparisons.
For my study, I am interested in how several different moderators affect the magnitude of the various treatment comparisons. I stumbled across a paper (Nixon, Bansback, & Brennan, 2007) that combines the mixed treatment comparison method with meta-regression. My problem is finding a good software implementation for this method (preferably an implementation in R, since I'm most familiar with R). As far as I can tell, the metafor package isn't able to handle mixed treatment comparisons. Does anybody know whether there's a package out there that's able to handle both mixed treatment comparisons and meta-regression?