[R] lme() F-values disagree with aov()

[William Simpson]

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