[R-sig-ME] Model fit after false convergence

[Luciano La Sala]

Dear R-crew, 

I am using lmer to fit a model for epidemiological data. I start from a saturated model containing all the main effects of interest (all with p < 0.25 in a bivariate screening) plus one random intercept (please see below). From there, I need to refine my model based on AIC criterion. 

As you can see below, I'm getting a convergence error after fitting the saturated model, which I don't know how to deal with. 
 
I read somewhere that this problem can be solved by adding "verbose = TRUE" in the model. After doing this, I get the output below. 

At this point my questions are: 

1. Are thses results worth trusting?

2. What does "verbose=T" do? If not added, the only thing I get is the "convergence error" message. If added, the model keeps running after the "convergence error" line.  

3. What do the strings of numbers after "0: ... ", "1: ..." and "2: ..." below represent? I'd never seen that before. 

4. The error message "Warning message: In mer_finalize(ans) : false convergence (8)" still shows up. Should I worry, or just disregard it and start simplifying my model from there on? 

5. I have only 196 observations, but 104 random effects. Maybe this is the problem?    

Thank you so much in advance!! 

Luciano 

CODE AND OUTPUT: 

> full.model1 <- lmer(Death~HatchOrder + Year + ClutchSize + EggBreadth + EggVolume + ClutchVolume + I(ClutchVolume^2) + Asynchrony + SibingCompetence + (1|NestID),family=binomial,1,verbose = TRUE)

0: 210.20372:  1.18952 -4.38021 -2.14958 -2.47874 -0.643502 0.412270 0.811849 -1.48282 -0.875658 -0.0777208 -0.677601 -0.0518550 -0.604514 0.0650300 -0.000209959  1.31029  1.03084

1: 210.10114:  1.18952 -4.38021 -2.14958 -2.47874 -0.643502 0.412270 0.811849 -1.48282 -0.875658 -0.0777208 -0.677601 -0.0518550 -0.604514 0.0650299 -0.000211591  1.31029  1.03084

2: 210.10114:  1.18952 -4.38021 -2.14958 -2.47874 -0.643502 0.412270 0.811849 -1.48282 -0.875658 -0.0777208 -0.677601 -0.0518550 -0.604514 0.0650299 -0.000211591  1.31029  1.03084

Warning message: In mer_finalize(ans) : false convergence (8)

> full.model1

Generalized linear mixed model fit by the Laplace approximation 
Formula: Death~HatchOrder+Year+ClutchSize+EggBreadth+EggVolume+ ClutchVolume+I(ClutchVolume^2)+Asynchrony+SiblingCompetence+(1|NestID) 

   Data: 1 
   AIC   BIC logLik deviance
 244.1 299.8 -105.1    210.1

Random effects:
 Groups Name        Variance Std.Dev.
 NestID (Intercept) 1.4150   1.1895  
Number of obs: 196, groups: NestID, 104

Fixed effects:
                       Estimate Std. Error z value Pr(>|z|)   
(Intercept)          -4.3802131  5.6178408 -0.7797  0.43557   
HatchOrderSecond     -2.1495845  1.2872835 -1.6699  0.09495 . 
HatchOrderThird      -2.4787439  1.8973058 -1.3065  0.19140   
Year2007             -0.6435022  0.4793135 -1.3425  0.17942   
ClutchSizeTwo-eggs    0.4122699  3.2797887  0.1257  0.89997   
ClutchSizeThree-eggs  0.8118488  4.9473010  0.1641  0.86965   
BreadthCATBLarge     -1.4828236  0.7150390 -2.0738  0.03810 * 
BreadthCATBMedium    -0.8756582  0.8789277 -0.9963  0.31911   
BreadthCATBSmall     -0.0777208  1.0925961 -0.0711  0.94329   
VolumeCATBLarge      -0.6776006  0.7200754 -0.9410  0.34670   
VolumeCATBMedium     -0.0518550  0.9619276 -0.0539  0.95701   
VolumeCATBSmall      -0.6045140  1.1920193 -0.5071  0.61206   
ClutchVolume          0.0650299  0.0828151  0.7852  0.43231   
I(ClutchVolume^2)    -0.0002116  0.0001869 -1.1318  0.25770   
Asynchrony            1.3102881  0.4369016  2.9990  0.00271 **
SibCompPresent        1.0308412  1.0857487  0.9494  0.34240   
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 




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