[R] Power of test
Peter Dalgaard
p.dalgaard at biostat.ku.dk
Fri Oct 27 23:12:13 CEST 2006
"Leeds, Mark (IED)" <Mark.Leeds at morganstanley.com> writes:
> I don't know if there is one but if you use the t.test with df greater than 30, you will
> Get answers very close to that for the normal because the tables get pretty close after
> df of 30. I guess to be safe you can use set df to some huge #.
>
Slightly awkward, you cannot set the df independently from n in
power.t.test. You can still cheat it by increasing n and sd (by a
factor of, say, 100 and 10 respectively).
Anyways, the power function for z tests is pretty much the code Ethan
started out with...
>
>
>
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Ethan Johnsons
> Sent: Friday, October 27, 2006 4:50 PM
> To: ONKELINX, Thierry
> Cc: r-help at stat.math.ethz.ch; Peter Dalgaard
> Subject: Re: [R] Power of test
>
> Can I please ask a quick question again on this?
>
> Is there a power test function for z-test? Obviuosly, ?power.z.test
> does not give me anything.
>
> thx much
>
> ej
>
> On 10/27/06, ONKELINX, Thierry <Thierry.ONKELINX at inbo.be> wrote:
> > A quick answer to your questions:
> >
> > 1. Since nobody knows the "true" delta. I prefer to calculate the power for a range of deltas. Most of the time for a range spanning - 2 * expected delta up to 2 * expected delta. This gives an idea on how the power changes if delta changes.
> > 2. ?power.t.test explains how to calculate n for a given power, delta, sd and sig.level. A quote from ?power.t.test: "Exactly one of the parameters 'n', 'delta', 'power', 'sd', and 'sig.level' must be passed as NULL, and that parameter is determined from the others."
> >
> > Cheers,
> >
> > Thierry
> >
> > ----------------------------------------------------------------------
> > ------
> >
> > ir. Thierry Onkelinx
> >
> > Instituut voor natuur- en bosonderzoek / Reseach Institute for Nature
> > and Forest
> >
> > Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
> > methodology and quality assurance
> >
> > Gaverstraat 4
> >
> > 9500 Geraardsbergen
> >
> > Belgium
> >
> > tel. + 32 54/436 185
> >
> > Thierry.Onkelinx at inbo.be
> >
> > www.inbo.be
> >
> >
> >
> > Do not put your faith in what statistics say until you have carefully
> > considered what they do not say. ~William W. Watt
> >
> > A statistical analysis, properly conducted, is a delicate dissection
> > of uncertainties, a surgery of suppositions. ~M.J.Moroney
> >
> >
> > -----Oorspronkelijk bericht-----
> > Van: r-help-bounces at stat.math.ethz.ch
> > [mailto:r-help-bounces at stat.math.ethz.ch] Namens Ethan Johnsons
> > Verzonden: vrijdag 27 oktober 2006 16:59
> > Aan: Peter Dalgaard
> > CC: r-help at stat.math.ethz.ch
> > Onderwerp: Re: [R] Power of test
> >
> > Thank you so mcuh for the explanation, Chuck & Peter.
> >
> > Two quick questions,please.
> >
> > It states that delta = True difference in means. When the true diff
> > is unkown, can you use the expected diff for delta.
> >
> > If you want to know the n (number of observations) off of power.t.test
> > to have i.e. 80% power, how do you calculate? Is there a way to do it
> > in R, or use algebra?
> >
> > power.t.test(n = NULL, delta = NULL, sd = 1, sig.level = 0.05,
> > power = NULL,
> > type = c("two.sample", "one.sample", "paired"),
> > alternative = c("two.sided", "one.sided"),
> > strict = FALSE)
> >
> > Thank you,
> >
> > ej
> >
> > On 27 Oct 2006 16:37:08 +0200, Peter Dalgaard <p.dalgaard at biostat.ku.dk> wrote:
> > > "Ethan Johnsons" <ethan.johnsons at gmail.com> writes:
> > >
> > > > What would be the R formulae for a two-sided test?
> > > >
> > > > I have a formula for a one-sided test:
> > > >
> > > > powertest <- function(a,m0,m1,n,s){
> > > > t1 = -qnorm(1-a)
> > > > num = abs(m0-m1) * sqrt(n)
> > > > t2 = num/s
> > > > pow = pnorm(t1 + t2)
> > > > }
> > > >
> > > > Would you pls let me know if you know of?
> > >
> > > (Notice that power.t.test does this more accurately)
> > >
> > > For practical purposes, just halve a. Perfectionists may want you to
> > > add pnorm(t1 - t2), so that the total power becomes a when t2 == 0.
> > >
> > > BTW: -qnorm(1-a)==qnorm(a)
> > >
> > > --
> > > O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
> > > c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
> > > (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
> > > ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
> > >
> >
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--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
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