Do glmer and glmmadmb calculate log likelihood on thesame scale ?

Just a note that those are not the same models.

Huh.

OR you could change glmmadmb() to

fm2 <- glmmadmb(y~Base*trt+Age+Visit+(Visit|subject),
 data=epil2, family="poisson", corStruct = "full")

however, on my machine, there are warnings about the matrix not being
positive definite, and the model never converges.

I haven't updated glmmADMB recently (0.6.4 2011-08-30), so it
gives the warning, but continues merrily to give:

             (Intercept)   Visit
(Intercept)     0.24931 0.24931
Visit           0.54572 0.54572

and the same likelihood as before

Log-likelihood: -655.41

glmer was
  Groups  Name        Variance Std.Dev. Corr
  subject (Intercept) 0.24912  0.49912
          Visit       0.53962  0.73459  0.011
  'log Lik.' -262.6586 (df=9)

Your suggestion Visit + (1 | Visit) + (0 + Visit | subject) 
gave me

  Groups  Name        Variance   Std.Dev.
  subject Visit       0.77301    0.87921
  Visit   (Intercept) 5.1845e-16 2.2769e-08
'log Lik.' -421.1128 (df=8)

I have to admit, the direction of the change in loglikelihood here 
confuses me a little ;)

My lme4 is also a little antiquated: 0.999375-42 (2011-10-02).

| David Duffy (MBBS PhD)                                         ,-_|\
| email: davidD at qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
| Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v