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re: st: power repeated measures anova vs mixed models


From   Ricardo Ovaldia <ovaldia@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   re: st: power repeated measures anova vs mixed models
Date   Thu, 24 May 2012 09:39:24 -0700 (PDT)

Thank you David.
I played with this a few day ago. The problem is that you have to make a lot of assumptions that I do not feel comfortably making because I lack prior knowledge about parameters, covariances, etc. The program produces very different results depending on what you "plug in".

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, 10:01 AM
> .
> 
> I just came across this software for longitudinal /
> hierarchical experimental design power analysis:
> 
> http://sitemaker.umich.edu/group-based/optimal_design_software
> 
> I've not used it, but it might help you avoid simulation.
> 
> -Dave
> 
> > Dear all,
> > 
> > I have been struggling to find an answer or reference
> to this problem.
> > 
> > I am planning a longitudinal analysis comparing 3
> groups with 6 time points per subject. The design is balance
> with 65 subjects for group. 
> > 
> > Because I do not have preliminary data and do not want
> to make unrealistic assumptions about the covariate
> structure and other parameters required to calculate power
> for mixed models, I decided to use repeated measures ANOVA
> to estimate the minimum detectable effect size at 80% power.
> 
> > My questions are, will the mixed model have more power
> that the repeated measures ANOVA in this case? Are there any
> references regarding these comparisons?
> > 
> > Thank you,
> > Ricardo
> > 
> > Ricardo Ovaldia, MS
> > Statistician 
> > Oklahoma City, OK
> 
> 
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