[R-sig-ME] glmmADMB error messages with percentage cover data (Elwyn Sharps)

[Elwyn Sharps]

Hi Alain, Thanks for your reply. Sorry I hadn't noticed this section of the glmmADMB help file and as some of the models were running fine, I assumed there wasn't a problem with the family. Have you got any other ideas on how I can deal with the very large number of zeros in the data? As it's percentage cover rather than count data, I don't think I can use Poisson or Neg Binomial. Thanks again
Elwyn

> Date: Wed, 19 Nov 2014 17:38:40 +0100
> From: highstat at highstat.com
> To: r-sig-mixed-models at r-project.org
> Subject: Re: [R-sig-ME] glmmADMB error messages with percentage cover data	(Elwyn Sharps)
> 
> 
> 
> >
> > I have collected data on % cover of a variety of
> > plant species on heathland (in relation to nesting birds) and am interested in
> > testing the effect of density of grazing ponies, the proximity to nest site
> > (%cover measured at 1 and 10m from the nest) and the age of the nest (as a
> > control for vegetation being measured at nests of different ages). The
> > response is percentage cover and contains many zeros (see attached
> > data for an example).
> >
> >
> > I have tried using glmmADMB, with family=
> > binomial and zero inflation=T. The response was created using cbind e.g.
> > y<-(cbind(Data$Plant_cover, Data$Plant_empty)), where Plant cover = % cover
> > and Plant empty = 100-Plant cover.
> >
> >
> > Example model:
> >
> > Fit1<-glmmadmb(y~Grazing*proximity+Age+(1|site),data=Heath,zeroInflation=TRUE,family="binomial")
> >
> 
> 
> See the help file of glmmadmb:
> 
> zeroInflation:   whether a zero-inflated model should be fitted (only 
> "poisson" and "nbinom" families).
> 
> With emphasis on the last part in this sentence.
> 
> Kind regards,
> 
> 
> Alain
> 
> 
> > The majority of the models for Species
> > 1 have been running fine, however I have been getting the occasional error
> > message and for Species 2, all models give an error message.
> >
> >
> > Example error messages:
> >
> > Parameters were estimated, but not standard errors
> > were not: the most likely problem is that the curvature at MLE was zero or
> > negative
> >
> > Error in glmmadmb(w ~ Grazing * proximity + Age + (1 | site), data =
> > heathland,  :
> >
> >    The function maximizer failed (couldn't find STD file) Troubleshooting
> > steps include (1) run with 'save.dir' set and inspect output files; (2) change
> > run parameters: see '?admbControl'
> >
> > Warning message:
> >
> > In glmmadmb(w ~ 1 + (1 | site), data = heathland, zeroInflation = T,  :
> >
> >    Convergence failed:log-likelihood of gradient= -0.269018
> >
> >
> >
> > I just wanted to check that this is a sensible
> > way to deal with these data and if there is anything that I should be doing to
> > remedy the error messages? I've tried some other options, e.g. Arc sine
> > transformation couldn't deal with the excess zeros. I've also considered
> > quasibinomial in lme4, but have seen Doug Bates comments on the unreliability
> > of the model output.
> >
> >   
> >
> > Any advice would be very much appreciated.
> > All the best
> > Elwyn 		 	   		   		 	   		
> >
> > ------------------------------
> >
> > _______________________________________________
> > R-sig-mixed-models mailing list
> > R-sig-mixed-models at r-project.org
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
> >
> > End of R-sig-mixed-models Digest, Vol 95, Issue 24
> > **************************************************
> >
> 
> -- 
> Dr. Alain F. Zuur
> 
> First author of:
> 1. Beginner's Guide to GAMM with R (2014).
> 2. Beginner's Guide to GLM and GLMM with R (2013).
> 3. Beginner's Guide to GAM with R (2012).
> 4. Zero Inflated Models and GLMM with R (2012).
> 5. A Beginner's Guide to R (2009).
> 6. Mixed effects models and extensions in ecology with R (2009).
> 7. Analysing Ecological Data (2007).
> 
> Highland Statistics Ltd.
> 9 St Clair Wynd
> UK - AB41 6DZ Newburgh
> Tel:   0044 1358 788177
> Email: highstat at highstat.com
> URL:   www.highstat.com
> 
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