Re: st: power repeated measures anova vs mixed models

[Ricardo Ovaldia <ovaldia@yahoo.com>]

Thank you David. Exactly what I needed, i.e. the similarity between RM ANOVA and -xtmixed- under certain conditions.

Ricardo.


Ricardo Ovaldia, MS
Statistician 
Oklahoma City, OK


--- On Thu, 5/24/12, Airey, David C <david.airey@vanderbilt.edu> wrote:

> From: Airey, David C <david.airey@vanderbilt.edu>
> Subject: Re: st: power repeated measures anova vs mixed models
> To: "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
> Date: Thursday, May 24, 2012, 5:44 PM
> .
> 
> I'm confused how someone could answer your question without
> as many qualifications 
> as assumptions you feel uncomfortable making? The question
> is sincere. Just trying 
> to understand. Maybe all those choices in the software are
> the reality. What effect 
> did you test? The group x time interaction? You don't say
> what the hypothesis was. 
> You say you don't want to assume what you don't know about
> the covariance structure 
> or variance or measurement error given the lack of pilot
> data, but you want to know if the 
> RM ANOVA is more powerful than the "mixed model". Did you
> mean -xtmixed-, because 
> -anova- can certainly do mixed models? You can reproduce the
> RM ANOVA results 
> (except t versus z tests for contrasts) by assuming a
> specific correlation structure, 
> etc. From my understanding, the split plot with sphericity
> assumption is a subset of 
> what xtmixed can do. So I'm assuming you would get the same
> answer with the same 
> model, using either -anova- or -xtmixed-, unless you made
> other assumptions that 
> made the model different than -anova-. Austin's paper does
> mention ignoring a level
> of the hierarchy, but I doubt that is relevant in this
> situation which is a designed
> experiment.
> 
> Cheers,
> 
> -Dave
> 
> 
> > You are missing the point. I have the sample size
> (n=65/group), power (80%)
> > and alpha (5%), 3 groups and 6 time points. What I want
> to compute is the minimal
> > detectable effect size. I did the power analysis using
> a repeated measure ANOVA and
> > obtained the minimal detectable effect sizes assuming
> various correlations between
> > the repeated measurements. What I want to know is
> whether the mixed model would
> > have more power to detect these effect sizes? 
> > 
> > Ricardo Ovaldia, MS
> > Statistician 
> > Oklahoma City, OK
> 
> 
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