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st: AW: repeated measures analysis: random mixed models, GEE and power analysis


From   "Baumeister Sebastian" <Baumeister@ift.de>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: AW: repeated measures analysis: random mixed models, GEE and power analysis
Date   Sat, 15 Dec 2007 15:51:03 +0100

Hi diego, 

here are some useful links to software that does sample size analysis for mixed models:

http://www.healthstats.org/rmass/

http://sitemaker.umich.edu/group-based/optimal_design_software

http://stat.gamma.rug.nl/multilevel.htm#progPINT


sebastian

-----Ursprüngliche Nachricht-----
Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Diego Bellavia
Gesendet: Samstag, 15. Dezember 2007 01:51
An: STATAlist
Betreff: st: repeated measures analysis: random mixed models, GEE and power analysis

Dear Statalisters, 

I am writing a grant proposal (time is an issue here) 
and by study design I will  have to analyze serial measurements 
in three predefined groups of patients (the outcome variable is continous). 
The time between each measure should be uniform in all the patients. 
I should have no problems to enroll more than 40 patients per group.

Here are the questions: 

1) What should I choose between Univariate ANOVA for repeated measures, MANOVA, random mixed models and general estimating equations, and why ? 

Personally, I am fascinated by GEE, but I am not sure this is the easiest/most efficient way to perform a  serial measurements analysis. 

2) What are the differences between random mixed models and GEE, if any ? 

3) I will have to perform a sample-size analysis as well: what I have is baseline mean and SD of the outcome (by previous study) and I should be able to 
get mean and SD at the second assessment (by previous pilot study), might you drive me on how to perform a power analysis in this setting ? 

Thank you always, 

Diego


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