[R] lme v. aov?
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
>> R-help at stat.math.ethz.ch mailing list
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