"Eusebio Arenal Guti?rrez" <use at eio.uva.es> writes:
> I want to fit the following model:
>
> > aov.madera <- aov(tiempo~producto/panel, data = madera)
> > anova(aov.madera)
> Analysis of Variance Table
>
> Response: tiempo
> Df Sum Sq Mean Sq F value Pr(>F)
> producto 2 93.631 46.815 63.0511 4.304e-07 ***
> producto:panel 9 43.533 4.837 6.5144 0.001881 **
> Residuals 12 8.910 0.742
> ---
> Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.'
0.1 ` ' 1
>
> As panel is random I would need
> ["producto", "Mean Sq"]/["producto:panel",
"Mean Sq"] in the cell
> ["producto", "F value"]
> and its p-value, that is
>
> > 46.815/4.837
> [1] 9.67852
> > 2*pf(46.815/4.837, 2, 9, lower.tail=FALSE)
> [1] 0.01143266
>
> How can I fit this model with lme function (of nlme)? What arguments have I
> to put in the random and group arguments?
Assuming that this is a 3x4x2 factorial layout, it would be easier to
use
summary(aov(tiempo~producto+Error(producto:panel), data = madera))
cf.
> pr<-gl(3,1,24)
> pa<-gl(4,3,24)
> y<-rnorm(24)
> summary(aov(y~pr+Error(pr:pa)))
Error: pr:pa
Df Sum Sq Mean Sq F value Pr(>F)
pr 2 6.5870 3.2935 3.2109 0.08861 .
Residuals 9 9.2316 1.0257
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1
` ' 1
Error: Within
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 12 16.6469 1.3872
With lme() it seems to be tricky to do the pa:pr interaction
as a groping, but you might do
> pa<-gl(12,1,24)
> lme(y~pr,random=~1|pa)
Linear mixed-effects model fit by REML
Data: NULL
Log-restricted-likelihood: -35.11024
Fixed: y ~ pr
(Intercept) pr2 pr3
0.5753093 -0.3784748 -1.2511397
Random effects:
Formula: ~1 | pa
(Intercept) Residual
StdDev: 1.669157e-53 1.110096
Number of Observations: 24
Number of Groups: 12 > anova(lme(y~pr,random=~1|pa))
numDF denDF F-value p-value
(Intercept) 1 12 0.0200734 0.8897
pr 2 9 2.6726312 0.1227
Notice that this is not the same as the balanced analysis, since the
pa random effect would have a negative variance in this case.
--
O__ ---- Peter Dalgaard Blegdamsvej 3
c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
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