[R-sig-ME] quasi-binomial family in lme4

[Douglas Bates]

On Tue, Nov 9, 2010 at 9:02 AM, Jarrod Hadfield <j.hadfield at ed.ac.uk> wrote:
> Hi Florian,
>
> This comes up regularly and the list (nearly) always stays silent. As far as
> I am aware quasi models in lmer do not, and never have, given sensible
> results. To model over-dispersion you can try fitting an observation-level
> random effect. For example:
>
> data$resid<-as.factor(1:dim(data)[1])
>
> and fitting (1|resid) in the model formula.
>
> This year  I have reviewed four papers that have used quasi models in lmer,
> and its no fun to tell the authors that their results may not be meaningful.
> To paraphrase an earlier post, why are they there if they do not work - it's
> irresponsible?

I agree.  I should have removed them from lme4 long ago if I suspected
that the results were not correct.

I will do so (once I figure out how to forbid them).

> On 8 Nov 2010, at 03:30, T. Florian Jaeger wrote:
>
>> Hi,
>> I am analyzing some data that seems to require a quasibinomial model,
>> but the model returns incredibly small standard errors (and
>> correspondingly inflated t-values) that do not seem to be justified
>> given my data.
>> I've been reading (I think) all available posts on problems with the
>> quasi-binomial family in lme4. But I can't judge from the posts
>> whether all issues with the  quasi-binomial models in lme4 are assumed
>> to be resolved. So, I am wondering, are there any known issues with
>> quasi-binomial models in lme4?
>>
>> I am using
>>
>> Package:            lme4
>> Version:            0.999375-35
>> Date:               2010-08-18
>>
>> in environment:
>>               _
>> platform       i386-pc-mingw32
>> arch           i386
>> os             mingw32
>> system         i386, mingw32
>> status
>> major          2
>> minor          11.1
>> year           2010
>> month          05
>> day            31
>> svn rev        52157
>> language       R
>> version.string R version 2.11.1 (2010-05-31)
>>
>> cheers,
>> Florian
>>
>> _______________________________________________
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>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
>
>
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