[R-sig-ME] Significant anova results for identical Models in glmer

[burg4401 at uni-trier.de]

Dear List,

when fitting two identical lmer Models and comparing them with 
anova() one Model has a significant p-value 
although obviously all coefficients and variances and likelihoods remain the 
same.

I think this comes from line 1000 in lmer.R (Rev 266)
pchisq(0,0,lower=F) == 0

I'm not concerned about someone putting in twice the same model, but 
apparently if two models with same degree of freedom are compared the pvalues 
are calculated on a dchisq(df=0) basis...
e.g. factor1 = SEX , factor2 = (higher than 1.78m)

Maybe I was looking in the wrong books, but I couldn't find an argument 
against this comparison. Could it be that the Problem lies in non nested 
parameter spaces?

Not least I'ld like to thank everyone in the list upcoming with interesting 
questions and answers. Overall many thanks to the programmers of lme4. Without 
lme4 I would have had problems to use my large matrices. Great Work.

Best Regards,
Pablo

Working example:
gm1 <- glmer(cbind(incidence, size - incidence) ~0+ period + (1 | herd), 
family = binomial, data = cbpp)

gm2 <- glmer(cbind(incidence, size - incidence) ~ -1 + period + (1 | herd), 
family = binomial, data = cbpp)

anova(gm1,gm2)             
Data: cbpp                   
Models:                      
gm1: cbind(incidence, size - incidence) ~ 0 + period + (1 | herd)
gm2: cbind(incidence, size - incidence) ~ -1 + period + (1 | herd)
    Df     AIC     BIC  logLik Chisq Chi Df Pr(>Chisq)            
gm1  5 110.096 120.223 -50.048                                    
gm2  5 110.096 120.223 -50.048     0      0  < 2.2e-16 ***        
---                                                               
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1