[R-sig-ME] [R] False convergence of a glmer model

[Shige Song]

Hi Ben,

As I stated earlier, Stata's xtlogit and xtmelogit did reach
convergence and gave reasonable results, so did MCMCglmm; so this
seems to be a unique problem with R's ML optimizer.

Shige

On Tue, Feb 16, 2010 at 7:00 PM, Ben Bolker <bolker at ufl.edu> wrote:
> Douglas Bates wrote:
>> On Tue, Feb 16, 2010 at 2:23 PM, Shige Song <shigesong at gmail.com> wrote:
>>> Dear Doug,
>>>
>>> Your argument makes a lot sense: after all, infant mortality is a rare
>>> event! I have two questions:
>>>
>>> 1) Is there a way to change the convergence criterion in a glmer model
>>> (to make it more tolerant)?
>>
>> I'm not sure that is a good idea.  If the linear predictor produces
>> probabilities that are so small that the deviance is insensitive to
>> the parameter values, what would it mean to quote estimates of those
>> parameters?
>>
>>> 2) Do you see a better approach than mixed logistic regression model
>>> in estimating infant morality, given the fact that infant mortality is
>>> a rare event?
>>
>> I don't know of other approaches myself.  Others on the list (Ben?)
>> may have suggestions.
>
>  I would think that a Bayesian approach would help here (by ruling out
> probabilities of exactly zero): however, generally harder to implement
> -- don't know if MCMCglmm offers possibilities for priors on fixed
> effect parameters -- WinBUGS (possibly via glmmBUGS), ADMB may be
> solutions.  (Also maybe harder to convince reviewers of.)
>
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