[R-sig-ME] Log likelihood of a glmer() binomial model .
r@turner @end|ng |rom @uck|@nd@@c@nz
Mon Apr 22 01:48:54 CEST 2019
On 22/04/19 4:27 AM, Juho Kristian Ruohonen wrote:
> Rolf: I'm no Prof but a lowly grad student of an unrelated field, so
> take all my input with a grain of salt.
Well, you will very likely *be* a Prof. someday. And your input seems
very sound to me. (I am a retired "Honorary" Research Fellow, which
seems to me to be even lowlier than a grad student; grad students
generally get at least a *bit* of monetary compensation, in the form of
scholarships or other stipends. :-) )
> As alluded to by Ben, predict() can certainly provide fitted
> probabilities for the validation set with the random effects taken into
> account. This is achieved by the re.form = NULL argument. However -- and
> I'll be happy to be corrected on this -- the problem is that dbinom()
> will calculate a (log)likelihood of the observed responses assuming a
> regular binomial PMF, which does not apply in the case of a
> mixed-effects model. Thus the result will not equal the loglikelihood
> that is maximized in the fitting process, i.e. will not equal
> logLik(validationFit) unless it's a standard logistic GLM.
Thanks. I'm going to have to chew this over a bit more .... Takes me a
while to get my head around these issues.
Honorary Research Fellow
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
More information about the R-sig-mixed-models