Nesting fixed factors in lme4 package
Martina Ozan <martina_ozan <at> hotmail.com> writes:
Hi, can anyone tell me how to nest two fixed factors using glmer in lme4? I have a split-plot design with two fixed factors - A (whole plot factor) and B (subplot factor), both with two levels. I want to do GLMM as I also want to include different plots as a random factor. But I am interested on the effect of A a B and their interaction on the response variable. I tried this:glmer(response~A*B+(A/B)+(1|C),data=Exp2,family=poisson but it gives the same output as if I removed (A/B) all together or used (A:B) instead thus the output is the same as: glmer(response~A*B+(1|C),data=Exp2,family=poisson anyone can help with how I define this nesting, so that data are analysed correctly given my split-plot design? thanks, Martina
In general mixed model questions should go to r-sig-mixed-models at r-project.org , but this is actually *not* specifically a mixed model problem. If A and B are fixed factors, you're typically interested in A*B, which translates to 1+A+B+A:B, i.e. intercept; main effects of A and of B; and the interaction. The nesting syntax A/B translates to 1 + A + A:B, i.e. no main effect of B. Nesting would typically make more sense in a random-effects context where the meaning of "B=1 in unit A=1" is different from "B=1 in unit A=2", i.e. where you don't want or it doesn't make sense to estimate a main effect of B across levels of A. Ben Bolker