
Dear Jarrod,

I went through some of the online discussions that you have made. However, I am very new to linear mixed model. I have a calf data consisting of treat(A &B),weeks (11),weight(wts) and subject (calf).
week	wts	treat	calf
w0	210	B	1
w0	230	B	2
I just wanted to fit a 3rd degree polynomial regression model with various correlation structures and want to select the best using AIC/BIC criteria.
please see the following code,

weekA<-indicator*week
Indicator<-1 for trt A,otherwise
wknum <- 1:11

ploy3.lme1<-lme(fixed=wts~poly(week,3)+poly(weekA,3),corr=corSymm(,form=~ wknum|calf),weights= varIdent (form=~|week),data=calfdata)
ploy3.lme2<-update(poly3.lme1,corr=corAR1(,form=~
 wknum|calf),weights= varIdent (form=~|week),data=calfdata)
select<-anova(poly3.lme1,poly3.lme3)


My questions are:
1.Am I on the right track?
2. If you are assuming heterogeneous within group variances for correlation structures ARH(1) or CSH),how do you specify the variance function by weights statement? and what are the form for those in corr=? (,form=~wknum|calf)

Thank you for your time and cooperation.I look forward to hearing from you at your earliest convenience.
Sincerely,
Tulsi Paudel
Mount Pleasant,Michigan







 		 	   		   		 	   		  
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