[R] lme v. aov?

John Christie jc at or.psychology.dal.ca
Thu Nov 27 19:46:22 CET 2003

Its not so much that I wasn't getting the difference between fixed and 
random effects.  Although, I do like the way you put the comment below. 
  For my purposes subject is a random effect.  It was more on correct 
notation in lme with repeated measures designs (my a and b are repeated 
while the mean subjectRT is between).  And, on whether the way aov 
treats repeated measures might best be called a MANOVA method.

On Nov 27, 2003, at 12:54 PM, Spencer Graves wrote:

>      Do you want to make inference about the specific subjects in your 
> study?  If yes, the subjects are a fixed effect.  If instead you want 
> to make inference about the societal processes that will generate the 
> subjects you will get in the future, that is a random effect.  The 
> function "lme" handles both fixed and random effects, as does 
> "varcomp".  The functions "aov" and "lm" are restricted to fixed 
> effects only.  You can use dummy coding for "lm" and "aov" as well.
>      The the distinction between "fixed" and "random" effects seems to 
> me to be the same as what Deming called the difference between 
> "enumerative" and "analytic" studies:  With a fixed effect / 
> enumerative study, the objective is to determine the disposition of 
> the sampling frame.  For example, Deming managed a survey of food 
> distribution in Japan in 1946 or so, right after World War II.  The 
> purpose was to determine where to deliver food the next day, etc., to 
> keep people from dying of starvation.  That was an enumerative study.  
> If the purpose had been to advance economic theories for use not only 
> in Japan or in 1946-47, that is an analytic study.
>      Do you have the book Pinhiero and Bates (2000) Mixed-Effects 
> Models in S and S-Plus (Springer)?  If you have more than one use for 
> analyzing data on human subjects, I suggest you get and study this 
> book if you haven't already.  Doug Bates and several of his graduate 
> students have developed "lme".  I am not current in the absolute 
> latest literature in that area of statistics, but Bates seems to me to 
> be among the leaders in that area and specifically in statistical 
> computing for that kind of problem.
>      hope this helps.  spencer graves
> John Christie wrote:
>> I am trying to understand better an analysis mean RT in various 
>> conditions in a within subjects design with the overall mean RT / 
>> subject as one of the factors.  LME seems to be the right way to do 
>> this. using something like m<- lme(rt~ a *b *subjectRT, random= 
>> ~1|subject) and then anova(m,type = "marginal").  My understanding is 
>> that lme is an easy interface for dummy coding variables and doing a 
>> multiple regression (and that could be wrong).  But, what is aov 
>> doing in this instance? MANOVA?  I also haven't been able to find 
>> anything really useful on what to properly assign to  "random" in the 
>> lme formula.  For repeated measures the use above is always in the 
>> examples.
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