# split plot MJ 24.2
split2 <- read.table("split2.dat",header=T)
split2$fert <- factor(split2$fert)
split2$moist <- factor(split2$moist)
split2$tray <- factor(split2$tray)

# split plot using block:fert as random effect
# see Venables & Ripley (1994, sec. 6.7) or Chambers & Hastie (1992, sec. 5.2.1)
spl2.bfit <- aov(yield~moist*fert+Error(tray),split2)
# note: nesting such as "moist/tray" appears to give erroneous values
print(summary(spl2.bfit))

# split plot using LME (Splus on ALPHA computers only)
# see Lindstrom & Bates (1988) JASA 83:1014-1022
library(nlme)
spl2.lme <- lme(yield~moist*fert,random=~tray,
	cluster=~tray, data=split2, est.method="RML", re.structure="identity")
print(summary(spl2.lme))
print(fitted.values(spl2.lme))