mt.reject              package:multtest              R Documentation

_I_d_e_n_t_i_t_y _a_n_d _n_u_m_b_e_r _o_f _r_e_j_e_c_t_e_d _h_y_p_o_t_h_e_s_e_s

_D_e_s_c_r_i_p_t_i_o_n:

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

_U_s_a_g_e:

     mt.reject(adjp, alpha)

_A_r_g_u_m_e_n_t_s:

    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.

_V_a_l_u_e:

     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.

_A_u_t_h_o_r(_s):

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

_S_e_e _A_l_s_o:

     'mt.maxT', 'mt.minP', 'mt.rawp2adjp', 'golub'.

_E_x_a_m_p_l_e_s:

     # 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