[R-sig-ME] glmmADMB

[Thierry Onkelinx]

Dear Silvia,

I presume that the values of AL and PE are constant within the site. Did
you sample different locations within each site simultaneous ? Or did you
sample the same location at each site but at different dates?
In case of different locations per site you can simplify your model to.
glm(cbind(n.present, n.absent) ~ AL + PE, family = binomial) With n.present
the number of present locations per site.

Best regards,

Thierry

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

2015-04-30 14:50 GMT+02:00 Silvia Rodríguez Fernández <sileiris op gmail.com>:

> Dear list members,
>
> I´m a PhD student in trouble. I´m running a mix effects model with a
> dependent variable (PA: presence/absence, 0/1), one fixed explanatory and
> continuous variable (AL: altitude), one fixed factor (PE: initially 16
> levels, but reduced to 4 to reduce complexity) and one random term (2421
> sites). Basically, the structure of a logistic regression but with a random
> term to prevent temporal pseudoreplication.
>
> > model1<-glmmadmb(PA~PE+AL+(1|site), family="binomial")
>
> My data are quite unbalanced becouse I´ve many more zeros than ones. I´ve
> tried making a random selection of absences but I get similar problems than
> when using the whole dataset.
>
> I´m getting an output of results in R, but also getting a warning of lack
> of convergence, such as:
>
> Convergence failed:log-likelihood of gradient= -0.0195034
>
>
> Can I trust my results in spite of the warning?
>
> What other alternatives do you suggest?
>
>
> I´ve tried with the classical lmer and glmer, and I also get convergence
> problems as expected.
>
> I´ve also tried with the MCMCglmm package, but I´ve problems with the
> specification of the priors.
>
>
> Any help is welcomed.
>
>
> Silvia
>
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