[R-sig-ME] lme4a, glmer and all that
bates at stat.wisc.edu
Thu Jun 24 17:29:44 CEST 2010
On Thu, Jun 24, 2010 at 8:38 AM, Mitchell Maltenfort <mmalten at gmail.com> wrote:
> Haven't seen anything new since his March 4 post indicating that a
> check vs Stata agreed with lme4, not lme4a.
Sorry, I should have followed up more publicly on that posting. There
was a difference in the results between lme4 and lme4a and I was
concerned that the problem was in lme4. It turns out that the problem
was in lme4a and has now been resolved.
Having said that, I have now encountered examples where lme4a
converges to a different and better optimum than does lme4.
All of the maximum likelihood estimation methods for mixed models end
up doing some kind of numerical optimization procedure. One of the
changes in lme4a is the use of the bobyqa optimizer from the minqa
package, as opposed to the nlminb optimizer in the stats package. I
feel that the bobyqa optimizer is more effective and often faster than
nlminb (although not always).
One of the big differences between linear mixed models and generalized
linear mixed models is the number of parameters in the general
optimizer problem. In linear mixed models one can "profile out" the
fixed-effects parameters and produce a much easier optimization
problem. For generalized linear mixed models profiling out the
fixed-effects produces only an approximate minimum. In the example
from Dave Atkins fitting a Poisson GLMM that has been discussed on
this list recently the differences were minimal and solving the
reduced problem was much faster (17 seconds versus 300 seconds) than
the full optimization problem. However, in the examples from the 2007
JSS paper by Doran, Bates, Bliese and Dowling
(http://http://www.jstatsoft.org/v20/i02) I have seen a substantially
better minimum deviance using the full optimization than using the
Bottom line is that the results from lme4 should be ok but lme4a, when
I get it all sorted out, can do better.
> On Wed, Jun 23, 2010 at 7:17 PM, Jeffrey Evans
> <Jeffrey.Evans at dartmouth.edu> wrote:
>> Can anyone provide a status update on Doug Bates' comment from March about
>> doubting parameter estimates from glmer in lme4?
>> A) Which version is suspect - version 32, it seems?
>> B) Des version 33 resolve this issue?
>> Many thanks,
>> Jeff Evans
>> Dartmouth College
>> In March Doug Bates wrote:
>> "Two further comments. It is only the results from fitting generalized
>> linear mixed models with the current lme4 that I have cause to doubt. The
>> results from linear mixed models do check out. "
>> R-sig-mixed-models at r-project.org mailing list
> R-sig-mixed-models at r-project.org mailing list
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