Ronaldo, Further to my previous posting on your Glycogen nested aov model.
Having read Douglas Bates' response and Reflected on his lmer analysis output of your aov nested model example as given.The Glycogen treatment has to be a Fixed Effect.If a 'treatment' isn't a Fixed Effect what is ? If Douglas Bates' lmer model is modified to treat Glycogen Treatment as a purely Fixed Effect,with Rat and the interaction Rat:Liver as random effects then-- > model.lmer<-lmer(Glycogen~Treatment+(1|Rat)+(1|Rat:Liver)) > summary(model.lmer) Linear mixed-effects model fit by REML Formula: Glycogen ~ Treatment + (1 | Rat) + (1 | Rat:Liver) AIC BIC logLik MLdeviance REMLdeviance 239.095 248.5961 -113.5475 238.5439 227.095 Random effects: Groups Name Variance Std.Dev. Rat:Liver (Intercept) 2.1238e-08 0.00014573 Rat (Intercept) 2.0609e+01 4.53976242 Residual 4.2476e+01 6.51733769 # of obs: 36, groups: Rat:Liver, 6; Rat, 2 Fixed effects: Estimate Std. Error DF t value Pr(>|t|) (Intercept) 140.5000 3.7208 33 37.7607 < 2.2e-16 *** Treatment2 10.5000 2.6607 33 3.9463 0.0003917 *** Treatment3 -5.3333 2.6607 33 -2.0045 0.0532798 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Correlation of Fixed Effects: (Intr) Trtmn2 Treatment2 -0.358 Treatment3 -0.358 0.500 > anova(model.lmer) Analysis of Variance Table Df Sum Sq Mean Sq Denom F value Pr(>F) Treatment 2 1557.56 778.78 33.00 18.335 4.419e-06 *** -------------------------------------------------------- which agrees with the aov model below. > model <- aov(Glycogen~Treatment+Error(Rat/Liver)) > summary(model) John -----Original Message----- From: John Wilkinson (pipex) [mailto:[EMAIL PROTECTED] Sent: 07 September 2005 12:04 PM To: "Ronaldo Reis-Jr." Cc: r-help Subject: Re: [R] Doubt about nested aov output Ronaldo , It looks as though you have specified your model incorrectly. In the Rats example ,the Treatment is the only fixed effect,Rat and Liver are random effects In aov testing for sig of 'Means' of Random Effects is pointless and that is why 'p' values are not given.Further more the interaction between a Random Effect and a Fixed Effect is also a Random Effect. The 'aov' with error structure terms output reflects this by only giving 'p' values to Fixed Effects and their interactions > model <- aov(Glycogen~Treatment+Error(Rat/Liver)) > summary(model) Error: Rat Df Sum Sq Mean Sq F value Pr(>F) #Rat is random effect Residuals 1 413.44 413.44 Error: Rat:Liver #Rat:Liver is Random effect Df Sum Sq Mean Sq F value Pr(>F) Residuals 4 164.444 41.111 Error: Within Df Sum Sq Mean Sq F value Pr(>F) Treatment 2 1557.56 778.78 18.251 8.437e-06 *** #Fixed effect Residuals 28 1194.78 42.67 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 I hope that this is of help. John ______________________________________________ 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