[ADMB Users] Convergence failed:log-likelihood of gradient=

[Håkon Holand]

Dear GlmmADMB-users,

I am running models with a binary respons variable (0/1) and wanted to see if there was a linear trend through time (day of the season 1-117). I am using individual identity as a random variable in all my models. I am currently using R 2.14.1 (64-bit) and glmmadmb v.0.7.2.5.
The problem is that when I run my simplest model : SYN ~ sesday + (1|RINGNR) family="binomial", I get the following warnings:


Warning messages:
1: In glmmadmb(SYN ~ sesday + (1 | RINGNR), family = "binomial", data = helgesmr) :
  Convergence failed:log-likelihood of gradient= -0.0461339
2: In print.glmmadmb(list(n = 1548L, q = 1103L, formula = SYN ~ sesday +  :
  Object has a large gradient component


Summary of the model:



Call:
glmmadmb(formula = SYN ~ sesday + (1 | RINGNR), data = helgesmr,
    family = "binomial")


Coefficients:
             Estimate Std. Error z value Pr(>|z|)
(Intercept) -13.14000    0.99477  -13.21  < 2e-16 ***
sesday        0.04878    0.00888    5.49  3.9e-08 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Number of observations: total=1548, RINGNR=1103
Random effect variance(s):
Group=RINGNR
            Variance StdDev
(Intercept)    249.3  15.79

Log-likelihood: -566.279



Is this a "overly cautious" warning from glmmadmb or a more serious problem?
I also have to say that when I add a second order term (sesday^2) everything works fine. I am just a bit curious why the "simpler" model ran into trouble.

I really like all the new functionality of glmmADMB so I would like to thank the
developers!

Cheers,

Håkon
---------------------------------------------------------
Håkon Holand, PhD.Student
Centre for Conservation Biology
Department of Biology
Norwegian University of Science and Technology
NO-7491 Trondheim
Norway
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