Kieran,
Thanks, I hadn't thought about the t-test approach you mention, but I
agree that simulation would be a better approach.
Graham
2009/10/9 Kieran McCaul <[email protected]>:
> ...
>
> I suppose this depends on what your alternate hypothesis is.
> If you're expecting a general shift in the distribution, then you could do a power calculation based on a t-test and see what sample size you come up with.
> A Mann-Whitney test will have more power than a t-test to detect a difference when the distributions are not Normal. Ergo, if you have enough power for a t-test, you'll have enough power for a Mann-Whitney.
>
> The down side of this is that you could end up with a sample size that is much greater than you actually need, but that depends on what the actual distribution looks like and what difference you are looking for.
>
> My preferred option would be to estimate the power by simulation.
>
>
> ______________________________________________
> Kieran McCaul MPH PhD
> WA Centre for Health & Ageing (M573)
> University of Western Australia
> Level 6, Ainslie House
> 48 Murray St
> Perth 6000
> Phone: (08) 9224-2701
> Fax: (08) 9224 8009
> email: [email protected]
> http://myprofile.cos.com/mccaul
> http://www.researcherid.com/rid/B-8751-2008
> ______________________________________________
> If you live to be one hundred, you've got it made.
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>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On Behalf Of Graham Smith
> Sent: Saturday, 10 October 2009 4:59 AM
> To: [email protected]
> Subject: st: Mann-Whitney/Wilcoxon power analysis
>
> Can anyone point me towards any help for doing a power analysis for a
> Mann-Whitney test (I'm still using v8 of stata if it matters)
>
> Many thanks,
>
> Graham
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