[R-sig-ME] variance structure

Ben Bolker bbolker at gmail.com
Wed Apr 6 03:51:01 CEST 2011

On 11-04-05 06:30 PM, Cristina Gomes wrote:
> Hello,
> I'm running a model where the response is normally distributed and has an excess 
> of zeros. Because I was familiar with the lmer package I used it to run a GLMM 
> on this response, and addressed the problem of the excess of zeros by running 
> two models: one with the response as a binary one, using the complete data set, 
> and another excluding all the zeros and using the remaining response values in a 
> Gaussian model. This seemed to work fine. However, a reviewer suggested using 
> the whole data set and a zero-inflated poisson error structure in the MCMCglmm 
> package. I don’t know if this is appropriate as my response are rates (grams of 
> meat consumed per hr of observation) and not discrete values.

  I would give advice on how to get zero-inflated models working with
MCMCglmm (mainly, see Ch 5 of the "CourseNotes" vignette that comes with
MCMCglmm, but I think the reviewer is wrong to think that you could use
a zero-inflated Poisson.  I think the way you did it is fine.  However,
if you *wanted* to be fancy you might (after careful reading of Ch 5,
and thought) be able to set up a zero-inflated normal model in MCMCglmm
in a way analogous to the way zero-inflated Poissons are set up.

  Ben Bolker

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