[R-sig-ME] Negative binomial mixed effects modeling
davidD at qimr.edu.au
Wed May 12 09:58:37 CEST 2010
On Wed, 12 May 2010, Ben Bolker wrote:
> David Duffy wrote:
>> On Tue, 11 May 2010, David Zajanc wrote:
>> If you have only a "single level" of random effects eg simple clusters,
>> then gamm() [mgcv] or spm() [SemiPar].
> I don't see how this works -- gamm() will do the family options from
> glm (including negative.binomial() from MASS with a *fixed*
> overdispersion/theta/k parameter, but not? estimating the overdispersion
> as part of the fitting process?), spm() doesn't seem to have a NB option?
> I would love to be wrong on this and corrected on it.
No you are right. I don't regard having to iterate mgcv's gamm() "by
hand" over theta to be a showstopper, though. My memory was just wrong
| David Duffy (MBBS PhD) ,-_|\
| email: davidD at qimr.edu.au ph: INT+61+7+3362-0217 fax: -0101 / *
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