Identity and number of rejected hypotheses
This function returns the identity and number of rejected hypotheses for several multiple testing procedures and different nominal Type I error rates.
mt.reject(adjp, alpha)
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
|
alpha |
A vector of nominal Type I error rates. |
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 |
Sandrine Dudoit, http://www.stat.berkeley.edu/~sandrine,
Yongchao Ge, yongchao.ge@mssm.edu.
# 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
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