Hi mixed modelers, I would like to contrast average slopes using predictions from an LMM model fit with MCMCglmm. In essence I want to do something analogous to lsmeans' lstrends() function. The predicted slopes are growth rates ...more below. I have 12 days of plant growth data for 10 closely related species at 2 temperatures. There are several individuals per species at each temperature, and they're fully randomized. I want to asses whether each species' growth rate differs between temperatures. What I mean by that is that I would like to contrast the average slopes for each species in control vs. cold temperature; these slopes are the growth rates. I am modeling the data in MCMCglmm so I can account for phylogeny and also to be able to try multi-response models (to jointly model the stem, plastochrons, root, etc). I am starting out with the stem length data and after trying different time dependencies settled on this 3rd degree polynomial model: stemLen ~ poly(day, 3, raw=TRUE) * treatment * species + (1 + day | indiv) where day is a numeric time variable, treatment a 2 level factor (control and cold), and species a 10 level factor. I have a slight idea of how I would go about contrasting the average slopes for each species and that I would use the predict.MCMCglmm() function, but I would really appreciate some guidance before I go down the wrong the wrong path. Thanks for your help! Dan.
Daniel Fulop, Ph.D. Postdoctoral Scholar Dept. Plant Biology, UC Davis Maloof Lab, Rm. 2220 Life Sciences Addition, One Shields Ave. Davis, CA 95616