Re: [R] between-within anova: aov and lme

From: Spencer Graves <>
Date: Wed 09 Aug 2006 - 21:32:17 EST

          I can't answer your question about 'aov', but have you tried the following with 'lme':


          This assumes that A, B, and C are fixed effects, either continuous variables or factors present at only a very few levels whose effects are not reasonably modeled as a random sample from some other distribution.   It also assumes that the effect of each level of subject can be reasonable modeled as a random adjustment to the intercept following a common distribution with mean 0 and variance = 'var.subj'.

           The function 'aov' is old and mostly obsoleted by 'nlme'. There may be things that can be done in 'aov' that can not be done more or less as easily and usually better and more generally with 'lme', but I'm not familiar with such cases.

          Your question suggests you may not be familiar with Pinheiro and Bates (2000) Mixed-Effects Models in S and S-Plus (Springer). The standard R distribution comes with a directory "~library\nlme\scripts" containing script files 'ch01.R', 'ch02.R', ..., 'ch06.R', and 'ch08.R'.   These contain R script files with the R code for each chapter in the book. I've learned a lot from walking through the script files line by line while reviewing the corresponding text in the book. Doing so protects me from problems with silly typographical errors as well as subtle problems where the S-Plus syntax in the book gives a different answer in R because of the few differences in the syntax between S-Plus and R.

	  Hope this helps.
	  Spencer Graves

William Simpson wrote:
> I have 2 questions on ANOVA with 1 between subjects factor and 2 within factors.
> 1. I am confused on how to do the analysis with aov because I have seen two examples
> on the web with different solutions.
> a) Jon Baron ( does
> 6.8.5 Example 5: Stevens pp. 468 - 474 (one between, two within)
> between: gp
> within: drug, dose
> aov(effect ~ gp * drug * dose + Error(subj/(dose*drug)), data=Ela.uni)
> b) Bill Venables answered a question on R help as follows.
> - factor A between subjects
> - factors B*C within subjects.
> aov(response ~ A*B*C + Error(subject), Kirk)
> "An alternative formula would be response ~ A/(B*C) + Error(subject), which
> would only change things by grouping together some of the sums of squares."
> -------------------------------------------------------
> SO: which should I do????
> aov(response ~ A*B*C + Error(subject), Kirk)
> aov(response ~ A/(B*C) + Error(subject), Kirk)
> aov(response ~ A*B*C + Error(subject/(B*C)), Kirk)
> --------------------------------------------------------
> 2. How would I do the analysis in lme()?
> Something like
> lme(response~A*B*C,random=~1|subject/(B*C))???
> Thanks very much for any help!
> Bill Simpson
> ______________________________________________
> mailing list
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code. mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Wed Aug 09 21:36:36 2006

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.1.8, at Wed 09 Aug 2006 - 22:20:09 EST.

Mailing list information is available at Please read the posting guide before posting to the list.