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...wether a mixed model is the best approach, and if so, what model specification to use? -- ----------------------------------------------------- Vennlig hilsen/Kind regards, Atle Torvik Kristiansen M.Sc. student Institutt for biologi (DU2-100) Realfagbygget NTNU 7491 Trondheim Norway Email: atletorvik at gmail.com atletorv at stud.ntnu.no

Hi, I have a dataset where the residual variance decreases with on one of the predictors (population size). Currently, the full model looks like this: prior<-list(R=list(V=1e-16, nu=-2),G1=list(V=diag(2), nu=2)) m<-MCMCglmm(response~poly(population size,2)*poly(other predictor,2)+time, random=~us(1+time):population, data=data, prior=prior) Basically, it's a random regression with