"Leeds, Mark (IED)" <[EMAIL PROTECTED]> 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: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Ethan Johnsons > Sent: Friday, October 27, 2006 4:50 PM > To: ONKELINX, Thierry > Cc: r-help@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 <[EMAIL PROTECTED]> 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 > > > > [EMAIL PROTECTED] > > > > 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: [EMAIL PROTECTED] > > [mailto:[EMAIL PROTECTED] Namens Ethan Johnsons > > Verzonden: vrijdag 27 oktober 2006 16:59 > > Aan: Peter Dalgaard > > CC: r-help@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 <[EMAIL PROTECTED]> wrote: > > > "Ethan Johnsons" <[EMAIL PROTECTED]> 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. 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