On Thu, 10 Nov 2005, Ruben Roa wrote: > A statistic is any real-valued or vector-valued function whose > domain includes the sample space of a random sample. The > p-value is a real-valued function and its domain includes the > sample space of a random sample. The p-value has a sampling > distribution. The code below, found with Google ("sampling distribution > of the p-value" "R command") shows the sampling > distribution of the p-value for a t-test of a mean when the null hypothesis > is true. > Ruben > > n<-18 > mu<-40 > pop.var<-100 > n.draw<-200 > alpha<-0.05 > draws<-matrix(rnorm(n.draw * n, mu, sqrt(pop.var)), n) > get.p.value<-function(x) t.test(x, mu = mu)$p.value > pvalues<-apply(draws, 2, get.p.value) > hist(pvalues) > sum(pvalues <= alpha) > [1] 6
The sampling distribution of a p-value when the null hypothesis is true can be given more simply by this R code: runif() That holds for any valid test, not just a t test, that produces p-values distributed continuously on [0,1]. Discrete distributions can't quite do that without special tweaking. Mike ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html