predict with newdata -- New version of MCMCglmm
Hi Dave, I did intend to make it part of the current version. The difficulty is that if the fixed predictors in newdata have less levels than those in data, then things like the intercept will have a different interpretation. If data and newdata could be guaranteed to have the same levels for fixed terms (and terms within a variance.function) then it would be more straightforward. I guess I could return an error if this was not the case, and allow predictions on newdata when these conditions were satisfied.... Cheers, Jarrod Quoting David Atkins <datkins at u.washington.edu> on Thu, 08 Nov 2012 16:18:36 -0800:
[Posting to list as others might be interested...] Jarrod-- Very cool to see the continued development of MCMCglmm. My typical use of predict() functions (across various R regression-based commands) involves generating predictions on newdata -- typically to help interpret models involving non-linear terms and/or interactions. As far as I can tell, the predict function in v2.17 of MCMCglmm does not yet incorporate new data. Any guess on when the newdata argument in predict.MCMCglmm might "come online"? cheers, Dave -- Dave Atkins, PhD Department of Psychiatry and Behavioral Science University of Washington datkins at u.washington.edu 206-616-3879 http://depts.washington.edu/cshrb/ "We are drowning in information and starving for knowledge." Rutherford Roger
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.