From: Doran, Harold <HDoran_at_air.org>

Date: Fri 28 Oct 2005 - 03:14:26 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Oct 28 04:35:15 2005

Date: Fri 28 Oct 2005 - 03:14:26 EST

I think what you're looking for is in anova()

> fm1 <- lmer(dv ~ IV ...)

> anova(fm1)

names(mca2)

[1] "Lignee" "Pollinisateur" "Rendement"

replications(Rendement ~ Lignee * Pollinisateur, data = mca2)

Lignee Pollinisateur Lignee:Pollinisateur 20 10 2

Of course, summary(aov(Rendement ~ Pollinisateur * Lignee, data = mca2)) gives wrong tests of random effects. But, summary(aov1 <- aov(Rendement ~ Error(Pollinisateur * Lignee), data = mca2)) gives no test at all, and I have to do it like this :

tab1 <- matrix(unlist(summary(aov1)), nc=5, byrow=T)[,1:3]

Femp <- c(tab1[1:3, 3]/tab1[c(3,3,4), 3])

names(Femp) <- c("Pollinisateur", "Lignee", "Interaction")

1 - pf(Femp, tab1[1:3,1], tab1[c(3,3,4),1])

With "lme4" package (I did'nt succeed in writing a working formula with lme from "nlme" package), I can "see" standard deviations of random effects (but don't know how to find them) with :

library(lme4)

summary(lmer(Rendement ~ (1 |Pollinisateur) + (1 | Lignee) + (1 |
Pollinisateur:Lignee), data=mca2))

but I can't get F tests.

Thanks in advance.

Best regards,

Jacques VESLOT

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri Oct 28 04:35:15 2005

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