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: [email protected] 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. K > (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 > ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 > ______________________________________________ [email protected] 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. ______________________________________________ [email protected] 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.
