Dear All, I wonder if anyone can please offer any advice on a model including 2 fixed effects and 1 random effect, as well as a covariate?
The experimental design is as follows: I have a two by two factor design, where the two factors, Age (A) and Group size (G), both have 2 levels (old or young, and 1 or 3 respectively), and I am interested in the effect of these factors upon a continuous Response variable (R). The data is from social insects, so the above design is repeated for several colonies. I think that Colony (C) should be a random factor, as they were taken from a larger pool of available colonies. Identification number (I) is different for each individual. Furthermore, I have a covariate, Mass (M), which could have an effect upon R. Do you know which of the below (if any) would be the most appropriate model please? model<-lme(R~A*G*M,random=~1|C/I) model<-lme(R~A*G+M,random=~1|C/I) or is it necessary to state that A and G are factors as below: model<-lme(R~as.factor(A)*as.factor(G)*M,random= ~1|C/I) model<-lme(R~as.factor(A)*as.factor(G)+M,random= ~1|C/I) Do you also please have any advice upon the effect it would have to change the order in which the factors and covariate are placed in the model? When I tried moving them around in the above models it changed the test statistics slightly. Many thanks in advance for any help you can give, itÂ’s very much appreciated. Sophie Armitage ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
