[R-sig-ME] over-dispersed Poisson with lmer -- a trick, with a catch?
David Atkins
datkins at u.washington.edu
Thu Jul 16 18:21:23 CEST 2009
Ben Bolker wrote:
> PS -- if MCMCglmm works, why not stop there? Do you absolutely need
> it to work in lme4?
Ben--
Thanks for the comments (and, yes, I am very hesitant to ever request
anything from Doug given the Herculean amount of work he has put into
developing lmer()... suppose I should take this opportunity to learn how
to build from sources).
As for the comment above, on the one hand, you're right. We've got a
solution that works. Moreover, a lot of our addictions data is
zero-inflated, and MCMCglmm() can handle that as well (again, thank you
Jarrod!).
However, I've been using lme/lmer for 12 years and am really comfortable
with it. In addition, it's sssssmoking fast, and some of our problems
get large. An alternative model with daily drinking reports for past 90
days on several hundred participants took a couple hours to fit in
MCMCglmm(). Now, it's great that we can fit the model, but speed does
count for something.
[Actually, as an aside, my colleague who uses Stata called me while the
over-dispersed model was running in Stata, "Eh, Dave, this is going to
take a while in Stata, any chance you could fit this in R?" ;)]
cheers, Dave
Dave Atkins, PhD
Research Associate Professor
Center for the Study of Health and Risk Behaviors
Department of Psychiatry and Behavioral Science
University of Washington
1100 NE 45th Street, Suite 300
Seattle, WA 98105
206-616-3879
datkins at u.washington.edu
More information about the R-sig-mixed-models
mailing list