HTH,
Chuck
On Mon, 26 Jan 2009, Adam D. I. Kramer wrote:
>
> 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
> > > > ______________________________________________
> > > R-help@r-project.org mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > PLEASE do read the posting guide >
> > http://www.R-project.org/posting-guide.html
> > > and provide commented, minimal, self-contained, reproducible code.
> > >
> >
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
Charles C. Berry (858) 534-2098
Dept of Family/Preventive
Medicine
E mailto:cbe...@tajo.ucsd.edu UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901
