mt.reject {multtest} | R Documentation

## Identity and number of rejected hypotheses

### Description

This function returns the identity and number of rejected hypotheses for several multiple testing procedures and different nominal Type I error rates.

### Usage

    mt.reject(adjp, alpha)

### Arguments

`adjp` | A matrix of adjusted p-values, with rows corresponding to hypotheses and columns to multiple testing procedures. This matrix could be obtained from the function `mt.rawp2adjp` .
`alpha` | A vector of nominal Type I error rates.

### Value

A list with components

`r` | A matrix containing the number of rejected hypotheses for several multiple testing procedures and different nominal Type I error rates. Rows correspond to Type I error rates and columns to multiple testing procedures.
`which` | A matrix of indicators for the rejection of individual hypotheses by different multiple testing procedures for a nominal Type I error rate `alpha[1]`. Rows correspond to hypotheses and columns to multiple testing procedures.

### Author(s)

Sandrine Dudoit, http://www.stat.berkeley.edu/~sandrine,
Yongchao Ge, yongchao.ge@mssm.edu.

### See Also

`mt.maxT`, `mt.minP`, `mt.rawp2adjp`, `golub`.

### Examples

    # Gene expression data from Golub et al. (1999)
    # To reduce computation time and for illustrative purposes, we condider only
    # the first 100 genes and use the default of B=10,000 permutations.
    # In general, one would need a much larger number of permutations
    # for microarray data.

    data(golub)
    smallgd<-golub[1:100,]
    classlabel<-golub.cl

    # Permutation unadjusted p-values and adjusted p-values for maxT procedure
    res<-mt.maxT(smallgd,classlabel)
    mt.reject(cbind(res$rawp,res$adjp),seq(0,1,0.1))$r

[Package multtest version 1.6.0 Index]