glmmADMB error messages with percentage cover data (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")

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


------------------------------

-- 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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