Subject: RE: [R] observed power
Bill.Venables@CMIS.CSIRO.AU
Date: Sat 27 Jan 2001 - 12:07:57 EST
Message-ID: <2B7F04539DAFD311B61D009027D0DDA20C3C30@roper-cv.qld.cmis.CSIRO.AU>
Peter Dalgaard BSA [mailto:p.dalgaard@biostat.ku.dk] wonders:
| Sent: Saturday, 27 January 2001 1:29
| To: Mark M. Span
| Cc: r-help@stat.math.ethz.ch
| Subject: Re: [R] observed power
|
|
| "Mark M. Span" <span@psy.uva.nl> writes:
|
| > Is there a way to obtain the observed power of an aov()?
| >
| > I perform an aov with one between and one within factor,
| > and would like to know the observed power of the tests,
| > both for the main effect and the interaction. I found the
| > package 'hpower', but sense there is a more convenient
| > possibility. Is there?
| >
| > thanks
| >
| > Mark M. Span
|
| What's "observed power"? If you mean the item that SPSS has by that
| name, I think you first have to convince us that that is a sensible
| thing to calculate...
If you ever do find out, Peter, let me know too, please. I was puzzled, but
a bit worried about showing my ignorance... I can only imagine it means an
estimate of the non-centrality parameter in which case it is a sensible
thing to have available since it is essentially the signal-to-noise ratio.
Actually the MLE is the F-statistic but the maximum *marginal* likelihood
estimate (based on the marginal distribution of the F-statistic itself) is
of more interest as it is closer to unbiased. In the case of the multiple
correlation coefficient, for example, this is (practically) what people call
the "adjusted R^2" statistic, where the adjustment is essentially a bias
correction. You can come up with simple analogues for non-central
chi-squared and non-central F of course, but they are again just simple
linear adjustments, unless you really want to get flash. (I wrote a couple
of papers on this stuff in the 70s so I have a kind of nostalgic affinity
for it...)
I would be more interested in these quantities optionally appearing
routinely on summary tables than, for example, the cute 'significance
stars'. But as for calling them the "observed power", I would definitely
caution against that. It encourages entirely the wrong idea of what power
really is. (For example, it is a function, not a quantity, and you don't
ever "observe" it in practice.)
Bill Venables.
-- Bill Venables, CSIRO/CMIS Environmetrics Project Email: Bill.Venables@cmis.csiro.au Phone: +61 7 3826 7251 Fax: +61 7 3826 7304 Postal: PO Box 120, Cleveland, Qld 4163, AUSTRALIA-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request@stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
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