R] observed power

Also to me, power is more an a priori concept, best estimated before
collecting the data. And a priori power analyses are definitely the best

to control beta error probabilities. However, sometimes it may be

to control the sample size, for example, when re-analyzing data sets that
have been collected by others, or even comparing between analysis within

experiment. In a case like this post hoc power analyses can make sense.

You magically 'feld' that I referred to the SPSS output of a ANOVA, as I
did. The manual of SPSS describes this as:

- Select Observed power to obtain the power of the test when the

hypothesis is set based on the observed value.

which is very non-informative to me.

The reason I wanted to compute this 'observed power' is to get an

weather my (non-significant) interaction is caused by the absence of an
effect (observed power = 'quite high') or because I have too little

to identify any effect.

Of course I can always make an SPSS sidestep to calculate this, and my

mail should not be interpreted as a critique to aov output nor as a

statement that an index for 'observed power' should be included in R. I

just wondering if something *like* this is available.

As for Peter Dalgaard's second mail: I am getting more and more convinced
that SPSS indeed 'plugs in' the sampling estimates into the power

From: "Peter Dalgaard BSA" <p.dalgaard at biostat.ku.dk>

"Mark M. Span" <span at 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

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...

--
   O__  ---- Peter Dalgaard             Blegdamsvej 3
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907