ranktruncated: Rank truncated p-Value procedure...
In mutoss: Unified multiple testing procedures

Description Usage Arguments Details Value Author(s) References Examples

Rank truncated p-Value procedure The program computes the exact distribution and with it the p-Value

1	ranktruncated(pValues, K, silent=FALSE)

`pValues`	Vector of p-Values (not sorted)
`K`	the number of hypotheses / p-Values being in w
`silent`	If true any output on the console will be suppressed.

This function computes the exact distribution of the product of at most K significant p-values of 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.

Used.pValue: List information about the used pValues; RTP: Test statistic and pValue

Frank Konietschke

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

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