[R-sig-ME] glmmadmb and time-effects

Luca Corlatti luca.corlatti at gmail.com
Sat Aug 10 11:16:23 CEST 2013

Dear all, 
I am trying to analyse the relationship between parasite burden and several internal and external variables, including testosterone, cortisol, age, minimum temperature, home range. I have 2 years of data, collected on a monthly basis.
My data are not normally distributed and overdispersed. I therefore fitted my global model as:
mod <- glmmadmb(parasite~testosterone + cortisol + age + Tmin + hr + age:testosterone + age:cortisol + (1|year:month) + (1|id), family="nbinom", data=mydata, ZeroInflation=FALSE)

Visual inspection of residuals suggest that the model fits the data adequately. 
Starting from here, I fitted a set of simpler models and ran a model selection and a model averaging of the competitive models. 

The parasite emission shows marked monthly variation but, clearly, all the independent variables as somewhat dependent on time as well, and if I included month (time) as a fixed factor in the model, I am afraid the effects of such variables would be diluted. I therefore decided to include time as a random factor (1|year:month), but I am not sure If this is a plausible choice.
Kind regards, 

More information about the R-sig-mixed-models mailing list