scalebypanelist          package:SensoMineR          R Documentation

_S_c_a_l_e _b_y _p_a_n_e_l_i_s_t

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

     Returns a data frame with entries the means of the products over
     the sessions for  the whole panel and for each panelist.

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

     scalebypanelist(matrice, center = TRUE, scale = FALSE, col.p, 
         col.j, firstvar, lastvar = ncol(matrice), method = "coeff")

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

 matrice: a data frame made up of at least two qualitative variables 
          (_product_, _panelist_) and a set of quantitative variables
          (sensory descriptors)

  center: boolean, if T scores given by panelists are centered

   scale: boolean, if T scores given by panelists are scaled to unit
          varaince

   col.p: the position of one categorical variables of interest (the
          _product_ variable)

   col.j: the position of one categorical variables of interest (the
          _panelist_ variable)

firstvar: the position of the first endogenous variable

 lastvar: the position of the last endogenous variable (by default the
          last column of 'donnee')

  method: the method to replace the missing values: "average" or
          "coeff"  (coefficients of the _product_ variable in the anova
          model)

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

     Returns a data frame of dimension (_p*(1+j),k+2_), where _p_ is
     the number of products, _j_ the number of panelists, and _k_ the
     number of sensory  descriptors (the first two variables correspond
     to the _panelist_ and the _product_ variables).  This data frame
     contains the means of the products over the sessions for  the
     whole panel and for each panelist (data may be scaled to unit
     variance or not, this  parameter is set by users).

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

     Franois Husson

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

     data(chocolates)
     res=scalebypanelist(sensochoc, col.p = 4, col.j = 1, firstvar = 5)
     res

