[R] F tests for random effect models

Jacques VESLOT jacques.veslot at cirad.fr
Fri Oct 28 07:22:44 CEST 2005


Thanks a lot, but :

 > anova(lmer(Rendement ~ (1 | Pollinisateur) + (1 | Lignee) + (1 | Pollinisateur : Lignee),
	data = mca2))
Analysis of Variance Table
Erreur dans ok[, -nc] : nombre de dimensions incorrect

It looks like working with at least one fixed effect but not with random effect models.


Jacques VESLOT



Doran, Harold a écrit :
> I think what you're looking for is in anova() 
> 
> 
>>fm1 <- lmer(dv ~ IV ...)
>>anova(fm1)
> 
> 
> 
> 
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Jacques VESLOT
> Sent: Thursday, October 27, 2005 2:22 AM
> To: R-help at 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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