[R] between-within anova: aov and lme

[Spencer Graves]

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

	  lme(response~A*B*C,random=~1|subject)

	  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 (http://www.psych.upenn.edu/~baron/rpsych/rpsych.html) 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
> 
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