Logistic regression with factorial effect
On Thu, 18 Nov 2010, Billy wrote:
Hello, I?d like to evaluate the temporal effect on the relationship between a continuous variable (e.g. size) and the probability of mate success. glm(success1 ~ size, family=binomial) -> test1.1 glmer(success1 ~ size + (1|ind), family=binomial) -> test2.1 glmer(success1 ~ size + month + (1|ind), family=binomial) -> test3.1 glmer(success1 ~ size : month + (1|ind), family=binomial) -> test4.1 However, the expected result is not observed in the output of all these models. Using a model selection approach and comparing the AIC values of all models, it seems that test1.1 model is the most likely.
You have kind of done something wrong. Consider m0: success ~ size + month + size:month [in R, size*month] m1: success ~ size:month Cheers, David Duffy.