If there were a canned function for power for a non-parametric test, I
would not trust it.  This is because there are many assumptions that would
need to be made and I would not know if those in a canned function were
reasonable for my study.

I would compute power by simulation.  Simulate data sets that match what
you think the real data will/may look like, analyze the simulated datasets
and see what proportion give significant results (that will be your power).
 You can do this for different sets of assumptions to get a  feel for how
the different assumptions affect your results.  This way you know exactly
what assumptions you are making to get your power.


On Tue, Jul 9, 2013 at 2:18 PM, Charles Determan Jr <deter088@umn.edu>wrote:

> Greetings,
>
> To calculate power for an ANOVA test I know I can use the pwr.anova.test()
> from the pwr package.  Is there a similar function for the nonparamentric
> equivalent, Kruskal-Wallis?  I have been searching but haven't come up with
> anything.
>
> Thanks,
>
> --
> Charles Determan
> Integrated Biosciences PhD Candidate
> University of Minnesota
>
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>
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-- 
Gregory (Greg) L. Snow Ph.D.
538280@gmail.com

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