Re: [R] problem in R for Linear mixed model~

From: Daniel Malter <daniel_at_umd.edu>
Date: Sun, 22 Jun 2008 22:22:46 -0400


Hi,

random=~1|B/C
C is nested in B

##Example

data=Oats
regress=lme(yield~nitro*Variety,data=Oats,random=~1|Block/Variety)
##i.e. variety is nested in block

summary(regress)
##End of example

Best,
Daniel



cuncta stricte discussurus

-----Ursprüngliche Nachricht-----
Von: r-help-bounces_at_r-project.org [mailto:r-help-bounces_at_r-project.org] Im Auftrag von Manli Yan
Gesendet: Sunday, June 22, 2008 9:30 PM
An: r-help_at_r-project.org
Betreff: [R] problem in R for Linear mixed model~

   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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