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\name{ranktruncated}
\alias{ranktruncated}
\title{Rank truncated p-Value procedure...}
\usage{ranktruncated(pValues, K, silent=FALSE)}
\description{Rank truncated p-Value procedure
The program computes the exact distribution and with it the p-Value}
\details{This function computes the exact distribution of the product of
at most K significant p-values of \eqn{L>K} observed p-values. Thus, one gets the
pvalue from the exact distribution. This has certain advantages for genomewide
association scans: K can be chosen on the basis of a hypothesised
disease model, and is independent of sample size. Furthermore,
the alternative hypothesis corresponds more closely to the
experimental situation where all loci have fixed effects.
Please note that this method is implemented with factorials and binomial coefficients and the computation becomes numerical instable for large number of p-values.}
\value{Used.pValue: List information about the used pValues; RTP: Test statistic and pValue}
\author{Frank Konietschke}
\references{Dubridge, F., Koeleman, B.P.C. (2003). Rank truncated product of P-values, with application to genomewide association scans. Genet Epidemiol. 2003 Dec;25(4):360-6}
\arguments{\item{pValues}{Vector of p-Values (not sorted)}
\item{K}{the number of hypotheses / p-Values being in w}
\item{silent}{If true any output on the console will be suppressed.}}
\examples{pvalues<-runif(10)
result <- ranktruncated(pvalues,K=2,silent=FALSE) # take the K=2 smallest pvalues
result <- ranktruncated(pvalues,K=2,silent=TRUE) # take the K=2 smallest pvalues
result <- ranktruncated(pvalues,K=5,silent=TRUE) # take the K=5 smallest pvalues}
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