Dear list, 

I'm fairly new with mixed models and just starting to use glmer. I have a very basic question, which seems so basic I,m almost embarrased to ask. 

I work with habitat use data (summarized binomial data) which I fitted in a mixed model of the binomial family with a random factor accounting for repeated sampling of the same individual.We simply want basic descriptions of the data - effects of sex and year on the proportion of time spent in each habitat.

The code is as follow (for a simple model without interaction):

Colony.glmerSexYear <- glmer(cbind(ColoYes.allnoF24, ColoNo.allnoF24) ~ year.coded + sex + (1| Bague), family=binomial, data=mydata)

I simply want to report the fact that my predictor 'year' (categorical, three levels) is not significant. if I use the anova command anova(Colony.glmerSexYear) I get an anova table with degrees of freedom and  F values, but no p values

Analysis of Variance Table
           Df Sum Sq Mean Sq F value
year.coded  2 6.8140  3.4070  3.4070
sex         1 9.0351  9.0351  9.0351 


What is the proper way to obtain those missing p values ? or should I not use this anova table at all ? I was also suggested to conduct a likelyhood ratio test, but I don't have enough statistical background (yet) to do this without external help. 


Thank you very much for your help,


Marie
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