Dear R users:
I just got confused some R code used in linear mixed model~
example,two factors,A, B,C,A is fixed ,B,C are random,and B is nested in
C,if I wannt to use linear mixed model,are the following code correct for
each case?
case1:want to know random effect of B,
case1<-lme(y~A*B*C,random=~B|C) where "B|C" stand for what?,mean B is
nested in C?
case2: how to wirte random effect of C?
case2<-lme(y~A*B*C,random=~C)? this doesnt work out,it seem it must have
somehing like #|$
case3.omitting the random effect for B from case1
case3<-update(case1,random=~1|C),so I just type 1,so the random effect of
B will be removed from the model,there only left random effect of c ,the
random effect I removed ,which include both random intercept and slope
,correct??
case4:omitting the random intercept
case4<-update(case1,random=B-1|C)
this code I got from some paper,it said by inputing B-1|C,then the random
intercept is removed,so,if I want to remove random slode,I input B-2|C,it
doesnt work out.
case5 :how to know the both random effect of B,and C,I dont know how to
wirtie this in R
.
And I am a little confused of these R code,especially the #|#
part,what deos this syntax really mean in LME package,
Thank you for your time~
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