madOutPair            package:factDesign            R Documentation

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_D_e_s_c_r_i_p_t_i_o_n:

     This function is intended to be used in conjunction with
     outlierPair.  After outlierPair detects a pair of replicate
     observations with a significantly large difference between the
     observations, madOutPair uses median absolute deviation criteria
     for determining if one of the replicates is a single outlier.

_U_s_a_g_e:

     madOutPair(x, whichPair, c = 4)

_A_r_g_u_m_e_n_t_s:

       x: A vector of observations. 

whichPair: A result of outlierPair, recording which pair has largest
          difference between replicate observations. 

       c: The number of median absolute deviations to be used as a
          cutoff for determining single outliers.  

_D_e_t_a_i_l_s:

     Once pairs with significantly large differences are identified
     using outlierPair, madOutPair is applied.  If only one of the
     tagged replicates falls outside the range of
     (med(x)-c*mad(x),med(x)+c*mad(x)), the observation is designated
     the single outlier.

_V_a_l_u_e:

     The index of the single outlier observation, or "NA" if no single
     outliers are detected.

_A_u_t_h_o_r(_s):

     Denise Scholtens

_R_e_f_e_r_e_n_c_e_s:

     Scholtens et al. Analyzing Factorial Designed Microarray
     Experiments.  Journal of Multivariate Analysis.  To appear.

_S_e_e _A_l_s_o:

     'outlierPair'

_E_x_a_m_p_l_e_s:

     data(estrogen)
     outP <- outlierPair(exprs(estrogen)[247,],INDEX=pData(estrogen))[["whichPair"]]
     madOutPair(exprs(estrogen)[247,],outP)
     outP <- outlierPair(exprs(estrogen)[495,],INDEX=pData(estrogen))[["whichPair"]]
     madOutPair(exprs(estrogen)[495,],outP)

