mt.teststat             package:multtest             R Documentation

_C_o_m_p_u_t_i_n_g _t_e_s_t _s_t_a_t_i_s_t_i_c_s _f_o_r _e_a_c_h _r_o_w _o_f _a _d_a_t_a _f_r_a_m_e

_D_e_s_c_r_i_p_t_i_o_n:

     These functions provide a convenient way to compute test
     statistics, e.g., two-sample Welch t-statistics, Wilcoxon
     statistics, F-statistics, paired t-statistics, block F-statistics,
     for each row of a data frame.

_U_s_a_g_e:

     mt.teststat(X,classlabel,test="t",na=.mt.naNUM,nonpara="n")
     mt.teststat.num.denum(X,classlabel,test="t",na=.mt.naNUM,nonpara="n")

_A_r_g_u_m_e_n_t_s:

       X: A data frame or matrix, with m rows corresponding to
          variables (hypotheses) andn columns to observations. In the
          case of gene  expression data, rows correspond to genes and
          columns to mRNA samples. The data can be read using
          'read.table'. 

classlabel: A vector of integers corresponding to observation (column)
          class labels. For k classes, the labels must be integers
          between 0 and k-1. For the 'blockf' test option, observations
          may be divided into n/k blocks of k observations each. The
          observations are ordered by block, and within each block,
          they are labeled using the integers 0 to k-1. 

    test: A character string specifying the statistic to be used to
          test the null hypothesis of no association between the
          variables and the class labels.
           If 'test="t"', the tests are based on two-sample Welch
          t-statistics (unequal variances).  
           If 'test="t.equalvar"', the tests are based on two-sample
          t-statistics with equal variance for the two samples. The
          square of the t-statistic is equal to an F-statistic for k=2. 
           If 'test="wilcoxon"', the tests are based on standardized
          rank sum Wilcoxon statistics.
           If 'test="f"', the tests are based on F-statistics.
           If 'test="pairt"', the tests are based on paired
          t-statistics. The square of the paired t-statistic is equal
          to a block F-statistic for k=2. 
           If 'test="blockf"', the tests are based on F-statistics
          which adjust for block differences (cf. two-way analysis of
          variance). 

      na: Code for missing values (the default is
          '.mt.naNUM=--93074815.62'). Entries with missing values will
          be ignored in the computation, i.e., test statistics will be
          based on a smaller sample size. This feature has not yet
          fully implemented. 

 nonpara: If 'nonpara'="y", nonparametric test statistics are computed
          based on ranked data. 
           If  'nonpara'="n", the original data are used.

_V_a_l_u_e:

     For 'mt.teststat', a vector of test statistics for each row
     (gene). 

      For 'mt.teststat.num.denum', a data frame with 


teststat.num: the numerator of the test statistics for each row,
          depending on the specific 'test' option.

teststat.denum: the denominator of the test statistics for each row,
          depending on the specific 'test' option.

_A_u_t_h_o_r(_s):

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

_S_e_e _A_l_s_o:

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

_E_x_a_m_p_l_e_s:

     # Gene expression data from Golub et al. (1999)
     data(golub)

     teststat<-mt.teststat(golub,golub.cl)
     qqnorm(teststat)
     qqline(teststat)

     tmp<-mt.teststat.num.denum(golub,golub.cl,test="t")
     num<-tmp$teststat.num
     denum<-tmp$teststat.denum
     plot(sqrt(denum),num)

     tmp<-mt.teststat.num.denum(golub,golub.cl,test="f")