[R-sig-ME] naive questions about model building and error output

[Luciano La Sala]

Dear R-experts,
Quite new to R on this end, so I hope toy can help me out here: 
    
I am running version 2.7.1 on Windows Vista. I have small dataset which consists of: 
    
# NestID: nest indicator for each chicken. Siblings sharing the same nest have the same nest indicator. 
    
# Chick: chick indicator consisting of a unique ID for each single chick. 
    
# Year: 1, 2.
    
# ClutchSize: 1-, 2- , 3-eggs.  
    
# HO: hatching order within each clutch (1, 2, 3 [first, second and third-hatched chick]).
    
# SibComp: sibling competence: present/ absent (0, 1)
    
# Death10: death at ten days post-hatch (0, 1)
    
In order to account for lack of independence at the nest level (many
chicks are nested in nest... aha!), I'd like to run a GLMM with random slopes and intercepts for nests.
    
Using lmer, my model for survival at 10 days, for example, would read (or not!) as follows: 
    
model1 <- lmer(Death10 ~ HO + ClutchSize + Sibcomp + Year + (HO+0|NestID) + (1|NestID), family=binomial, 1)    
      
summary(model)

The output give me the following error: 

Error en mer_finalize(ans, verbose) : q = 416 > n = 198 

1. Whay does this error mean? I was told that my model fails to converge. 

2. If so, is there any solution to a lack of convergence?

3. Maybe I could use a model with only random intercept (See below)?

model2 <-lmer(Death10 ~ HO + ClutchSize + Sibcomp + Year + (1|NestID), family=binomial, 1)

I look forward to receiving your two cent’s worth. 

Best, Luciano   



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