I am trying to run a repeated measures glmm with a fixed intercept at 0 for a longitudinal study calculating the spread of a parasite within different genotypes of Daphnia hosts, and testing for a gxg effect between parasite strain and host strain. What I am curious about is how having a fixed intercept would interact with my random effect terms.
What I have now for my model is:
y <- cbind(infected, uninfected) glmer(y ~ Days*Genotype-1+(Day|Population), family=binomial, data)
Days represent the days I sampled and checked for infected/uninfected,
Genotype are my strains of Daphnia and
Population are the populations of Daphnia I have in the experiment. I am aware that there is some contention about having a fixed intercept, but I am using it as all populations must have started with no infection. Would this model be appropriate for answering my main question?