Benjamin Caldwell <btcaldwell <at> berkeley.edu> writes: > > Sub: using glmer to fit a mixed-effects model with gamma-distributed > response variable > > Hello, > I'm currently trying to fit a mixed effects model , i.e.: > > > burnedmodel1.2<-glmer(gpost.f.crwn.length~lg.shigo.av+dbh+leaf.area+ > bark.thick.bh+ht.any+ht.alive+(1|site/transect/plot), family=gaussian, > na.action=na.omit, data=rws30.BL)
[stuff about turning site, transect, plot into factors snipped] > > burnedmodel1.2<-glmer(gpost.f.crwn.length~lg.shigo.av+dbh+leaf.area+ > bark.thick.bh+ht.any+ht.alive+(1|site/transect/plot), family=Gamma, > na.action=na.omit, data=rws30.BL) > Alas, Gamma GLMMs are not yet feasible in glmer -- this is in the works but I wouldn't hold my breath (try searching the r-sig-mixed-model archives for this topic). At this point your options are somewhat limited, to 'build your own model' tools such as WinBUGS or AD Model Builder (it is conceivable that Gamma GLMMs could be added in the development version of glmmADMB, but again I wouldn't hold my breath). If I may ask, is there a reason you need Gamma GLMMs and not log-normal GLMMs? At least qualitatively, the properties of Gamma and lognormal distributions are reasonably similar (2-parameter families, domain = non-negative reals, distribution ranges from 'L-shaped' to approximately normal ...) You can fit a log-normal GLMM by simply log-transforming your data (dealing with zeros appropriately) and fitted a regular, linear mixed model ... Further discussions on this topic would probably be better on the r-sig-mixed-models list. Ben Bolker ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
