I have used lme() on data from a between-within subjects experiment. The correct ANOVA table is known because this is a textbook example (Experimental Design by Roger Kirk Chapter 12: Split-Plot Factorial Design). The lme() F-values differ from the known results. Please help me understand why.
d<-read.table("kirkspf2.dat",header=TRUE) for(j in 1:4) d[,j] <- factor(d[,j]) ### Make vars into type "factor" ##lme() results library(nlme) fit<-lme(y~a*b*c,random=~1|s, data=d) anova(fit) ##correct anova table ##subjects are nested within a; a between, b & c within fit2<-aov(y ~ a*b*c + Error(s/(c*b)), data=d) summary(fit2) I suspect I need a different random=... statement in lme(). Thanks very much for any help Bill The data file is attached -- kirkspf2.dat Here it is again: s a c b y 1 1 1 1 3 1 1 1 2 7 1 1 2 1 4 1 1 2 2 7 2 1 1 1 6 2 1 1 2 8 2 1 2 1 5 2 1 2 2 8 3 1 1 1 3 3 1 1 2 7 3 1 2 1 4 3 1 2 2 9 4 1 1 1 3 4 1 1 2 6 4 1 2 1 3 4 1 2 2 8 5 2 1 1 1 5 2 1 2 5 5 2 2 1 2 5 2 2 2 10 6 2 1 1 2 6 2 1 2 6 6 2 2 1 3 6 2 2 2 10 7 2 1 1 2 7 2 1 2 5 7 2 2 1 4 7 2 2 2 9 8 2 1 1 2 8 2 1 2 6 8 2 2 1 3 8 2 2 2 11
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