In a number of cases I want to use mixed-model ANOVA tests where I am interested in whether both the fixed and random effects (and their interactions) are significant.
If I use this example >library(nlme) >data(Orthodont) >anova(lme(distance ~ age + Sex, data = Orthodont, random = ~ 1)) I get the result numDF denDF F-value p-value (Intercept) 1 80 4123.156 <.0001 age 1 80 114.838 <.0001 Sex 1 25 9.292 0.0054 How do I also get a significance value for the random factor (Subject)? Incidentally, why does it seem that people are not generally interested in whether the random variables are different from each other? In the case of the Orthodont data (if there was replication at the Subject level i.e. if you could clone humans [as you can plants]), would it not be interesting to know if subjects (nested within sex) are different to each other as well as if there is an age effect (so to know if underlying genotype is also an important factor)? Thanks Nat Street -- Nathaniel Street Umeå Plant Science Centre Department of Plant Physiology University of Umeå SE-901 87 Umeå SWEDEN email: [EMAIL PROTECTED] tel: +46-90-786 5477 fax: +46-90-786 6676 www.upsc.se http://www.citeulike.org/user/natstreet ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.