Re: [R] F tests for random effect models

From: Doran, Harold <HDoran_at_air.org>
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)

-----Original Message-----
From: r-help-bounces@stat.math.ethz.ch
[mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Jacques VESLOT Sent: Thursday, October 27, 2005 2:22 AM To: R-help@stat.math.ethz.ch
Subject: [R] F tests for random effect models

Dear R-users,

My question is how to get right F tests for random effects in random effect models (I hope this question has not been answered too many times yet - I didn't find an answer in rhelp archives).

My data are in mca2 (enc.) :

names(mca2)
[1] "Lignee" "Pollinisateur" "Rendement"

dim(mca2)
[1] 100 3

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



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