[R] GLMs: Negative Binomial family in R?

Anders Nielsen anielsen at math.ku.dk
Tue Apr 5 21:01:42 CEST 2005


Hi,

Also consider using the function supplied in the post:

https://stat.ethz.ch/pipermail/r-help/2005-March/066752.html

for fitting negative binomial mixed effects models.

Cheers,

Anders.


On Tue, 5 Apr 2005, Achim Zeileis wrote:

> On Tue,  5 Apr 2005 11:20:37 -0600 nflynn at ualberta.ca wrote:
>
> > Greetings R Users!
> >
> > I have a data set of count responses for which I have made repeated
> > observations on the experimental units (stream reaches) over two air
> > photo dates, hence the mixed effect.  I have been using Dr. Jim
> > Lindsey's GLMM function found in his"repeated" measures package with
> > the "poisson" family.
> >
> > My problem though is that I don't think the poisson distribution is
> > the right one to discribe my data which is overdispersed; the variance
> > is greater than the mean.  I have read that the "negative binomial"
> > regression models can account for some of the differences among
> > observations by adding in a error term that independent of the the
> > covariates.
>
> glm.nb() from package MASS fits negative binomial GLMs.
>
> > I haven't yet come across a mixed effects model that can use the
> > "negative binomial" distribution.
>
> For known theta, you can plug negative.binomial(theta) into glmmPQL()
> for example. (Both functions are also available in MASS.) I'm not sure
> whether there is also code available for unknown theta.
>
> > If any of you know of such a function - I will certainly look forward
> > to hearing from you!  Additionally, if any of you have insight on
> > zero-inflated data, and testing for this, I'd be interested in your
> > comments too.  I'll post a summary of your responses to this list.
>
> Look at package zicounts for zero-inflated Poisson and NB models. For
> these models, there is also code available at
>   http://pscl.stanford.edu/content.html
> which also hosts code for hurdle models.
>
> hth,
> Z
>
> > Best Regards,
> > Nadele Flynn, M.Sc. candidate.
> > University of Alberta
> >
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