[R] Power analysis for MANOVA?

[Adam D. I. Kramer]

On Mon, 26 Jan 2009, Stephan Kolassa wrote:

> My (and, judging from previous traffic on R-help about power analyses,
> also some other people's) preferred approach is to simply simulate an
> effect size you would like to detect a couple of thousand times, run your
> proposed analysis and look how often you get significance.  In your simple
> case, this should be quite easy.

I actually don't have much experience running monte-carlo designs like
this...so while I'd certainly prefer a bootstrapping method like this one,
simulating the effect size given my constraints isn't something I've done
before.

The MANOVA procedure takes 5 dependent variables, and determines what
combination of the variables best discriminates the two levels of my
independent variable...then the discrimination rate is represented in the
statistic (Pillai's V=.00019), which is then tested (F[5,18653] = 0.71).  So
coming up with a set of constraints that would produce V=.00019 given my
data set doesn't quite sound trivial...so I'll go for the "par" library
reference mentioned earlier before I try this.  That said, if anyone can
refer me to a tool that will help me out (or an instruction manual for RNG),
I'd also be much obliged.

Many thanks,
Adam


>
> HTH,
> Stephan
>
>
> Adam D. I. Kramer schrieb:
>> Hello,
>>
>>     I have searched and failed for a program or script or method to
>> conduct a power analysis for a MANOVA. My interest is a fairly simple case
>> of 5 dependent variables and a single two-level categorical predictor
>> (though the categories aren't balanced).
>>
>>     If anybody happens to know of a script that will do this in R, I'd
>> love to know of it! Otherwise, I'll see about writing one myself.
>>
>>     What I currently see is this, from help.search("power"):
>> 
>> stats::power.anova.test
>>                         Power calculations for balanced one-way
>>                         analysis of variance tests
>> stats::power.prop.test
>>                         Power calculations two sample test for
>>                         proportions
>> stats::power.t.test     Power calculations for one and two sample t
>>                         tests
>>
>>     Any references on power in MANOVA would also be helpful, though of
>> course I will do my own lit search for them myself.
>> 
>> Cordially,
>> Adam D. I. Kramer
>> 
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>> 
>
>