Hello Simone,

Given that your response variable is binary and, consequently, you should
use generalized models, just occurs to me a comparison between a Generalized
Linear Model (the model without the random effect) and a Generalized Linear
Mixed Model (the model with the random effect).

You could write them as follows:

no.random.model <- glm(sex ~ hwp + hcp, data = mydata, family=binomial)
random.model <- glmer(sex ~ hwp + hcp + (1 | colony), data = mydata,
family=binomial)

My only doubt here is if one can directly compare both models, built under
different algorithms and from different packages.
Furthermore, I have no idea if the function 'anova' is able to compare
models produced by the 'glmer' function. One possibility is to compare them
based on Akaike Information Criteria (AIC) or any one of its corrected
versions.

I hope it helps you.
best wishes

-- 
Gustavo Requena
PhD student - Laboratory of Arthropod Behavior and Evolution
Universidade de São Paulo
Correspondence adress:
a/c Glauco Machado
Departamento de Ecologia - IBUSP
Rua do Matão - Travessa 14 no 321 Cidade Universitária, São Paulo - SP,
Brasil
CEP 05508-900
Phone number: 55 11 3091-7488

http://ecologia.ib.usp.br/opilio/gustavo.html

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