I've got a set of multivariate regression models, with weights, that I'm trying to compare in R. Looks like:
f0 <- lm(cbind(Y1,Y2,Y3,Y4) ~ co1 + co2 + co3 + co4 + x1, dat, weight=wt) f1 <- lm(cbind(Y1,Y2,Y3,Y4) ~ co1 + co2 + co3 + co4 + x1 + x2, dat, weight=wt) f2 <- lm(cbind(Y1,Y2,Y3,Y4) ~ co1 + co2 + co3 + co4 + x1 + poly(x2,2), dat, weight=wt)
I get perfectly reasonable and interpretable fits, but I'd like to be able to answer a question like, "overall, is there an effect of x2 on the dependent measures?" In other contexts, with nested models, I've done something like:
anova(f0, f1, f2)
and used a Chi-square test. But in this case, I get this error:
Error in SSD.mlm(object) : 'mlm' objects with weights are not supported
So, what alternatives do I have to compare these models? Thanks!