Re: st: power repeated measures anova vs mixed models

[Austin Nichols <austinnichols@gmail.com>]

Ricardo Ovaldia <ovaldia@yahoo.com>:
Did you look at page 6 of the link? Any of the references?

On Thu, May 24, 2012 at 1:45 PM, Ricardo Ovaldia <ovaldia@yahoo.com> wrote:
>
> Thank you Austin for the insightful remark: "Of course what you plug in matters"
>
> 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
>
>
> --- On Thu, 5/24/12, Austin Nichols <austinnichols@gmail.com> wrote:
>
>> From: Austin Nichols <austinnichols@gmail.com>
>> Subject: Re: st: power repeated measures anova vs mixed models
>> To: statalist@hsphsun2.harvard.edu
>> Date: Thursday, May 24, 2012, 11:59 AM
>> Ricardo Ovaldia <ovaldia@yahoo.com>:
>> Of course what you plug in matters--see also:
>> http://www.urban.org/UploadedPDF/1001394-clustered-randomization.pdf
>> (esp. page 6) and references therein.
>> You need estimates for the relevant information before you
>> can estimate power.
>>
>> On Thu, May 24, 2012 at 12:39 PM, Ricardo Ovaldia <ovaldia@yahoo.com>
>> wrote:
>> > 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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