Trying to make a nested lme analysis

Hi,

I'm trying to understand the lme output and procedure.
I'm using the Crawley's book.

I'm try to analyse the rats example take from Sokal and Rohlf (1995).
I make a nested analysis using aov following the book.

summary(rats)

    Glycogen       Treatment      Rat          Liver  
 Min.   :125.0   Min.   :1   Min.   :1.0   Min.   :1  
 1st Qu.:135.8   1st Qu.:1   1st Qu.:1.0   1st Qu.:1  
 Median :141.0   Median :2   Median :1.5   Median :2  
 Mean   :142.2   Mean   :2   Mean   :1.5   Mean   :2  
 3rd Qu.:150.0   3rd Qu.:3   3rd Qu.:2.0   3rd Qu.:3  
 Max.   :162.0   Max.   :3   Max.   :2.0   Max.   :3  

attach(rats)
Treatment <- factor(Treatment)
Rat <- factor(Rat)
Liver <- factor(Liver)

model <- aov(Glycogen~Treatment/Rat/Liver+Error(Treatment/Rat/Liver))
summary(model)

Error: Treatment
          Df  Sum Sq Mean Sq
Treatment  2 1557.56  778.78

Error: Treatment:Rat
              Df Sum Sq Mean Sq
Treatment:Rat  3 797.67  265.89

Error: Treatment:Rat:Liver
                    Df Sum Sq Mean Sq
Treatment:Rat:Liver 12  594.0    49.5

Error: Within
          Df Sum Sq Mean Sq F value Pr(>F)
Residuals 18 381.00   21.17               

OK,

Then I try to make this analysis using lme.

model <- lme(Glycogen~Treatment, random=~1|Treatment/Rat/Liver)
summary(model)

Linear mixed-effects model fit by REML
 Data: NULL 
       AIC      BIC    logLik
  233.6213 244.0968 -109.8106

Random effects:
 Formula: ~1 | Treatment
        (Intercept)
StdDev:    3.541272

 Formula: ~1 | Rat %in% Treatment
        (Intercept)
StdDev:     6.00658

 Formula: ~1 | Liver %in% Rat %in% Treatment
        (Intercept) Residual
StdDev:    3.764883 4.600247

Fixed effects: Glycogen ~ Treatment 
Error in if (any(wchLv <- (as.double(levels(xtTab[, wchPval])) == 0))) { : 
	missing value where logical needed
In addition: Warning message: 
NaNs produced in: pt(q, df, lower.tail, log.p) 

The random effects are correct, the variance component is OK:

In nested aov | In nested lme
Residual
21.1666       | 21.16227
Liver in Rats
14.16667      | 14.17434
Rats in Treatment
36.0648       | 36.079

But I not understand why the Fixed effects error?

What is the problem in my formula to make this analysis using lme?

Thanks for all
Inte
Ronaldo
-- 
Anger kills as surely as the other vices.
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