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Dear R users, I have a problem in plotting 3 dimensional graph using mixed models. My model is sur_prop ~ afr_c+I(afr_c^2)+I(afr_c^3)+byear_c+I(byear_c^2)+I(byear_c^3)+I(byear_c^4)+(1|Studyparish)+afr_c:byear_c +afr_c:I(byear_c^2)+afr_c:I(byear_c^3)+afr_c:I(byear_c^4)+I(afr_c^2):byear_c+I(afr_c^2):I(byear_c^2)+I(afr_c^2):I(byear_c^3)+I(afr_c^2):I(byear_c^4) This is a study on the effect of mothers' age and cohort year on children's survival. I can extract predicted value using a s...

...ticollinearity does not matter much. However, I am using mixed model to interpret something, so I am wondering if there is a suitable method to deal with this problem in lmer. My model is: model2<-lmer(sur_prop~(kidc+I(kidc^2)+I(kidc^3))*(byear_c+I(byear_c^2) +I(byear_c^3)+I(byear_c^4))+(byear_c|Studyparish),family=binomial) This is the maximum model and I have not begun to simplify it. The model is used to interpret the pattern how a mother's cohort year and total number of children will affect average survival rate of her children. Kids and byear_c have been centered, so the problem of correlati...