descript                 package:ltm                 R Documentation

_D_e_s_c_r_i_p_t_i_v_e _S_t_a_t_i_s_t_i_c_s _f_o_r _R_e_s_p_o_n_s_e _M_a_t_r_i_c_e_s

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

     Computes the percentages of positive and negative responses for
     each item, as well  the pairwise associations between items (see
     Details for more info).

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

     descript(X, n.print = 10, ..., print = TRUE)

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

       X: a data.frame containing binary variables. 

 n.print: if 'print=TRUE' gives the number of pairwise associations
          with the highest p-values to be printed. 

     ...: extra argument passed to 'chisq.test' (e.g.,
          'simulate.p.value', 'B') 

   print: logical; if 'TRUE' the results are printed.

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

     Before an analysis with latent variable models, it is useful to
     inspect the data for evidence of positive correlations. In the
     case of binary data, this ad hoc check can be performed by
     constructing  the 2 by 2 contingency tables for all possible pairs
     of items and examine the chi-squared p-values.

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

     If 'print=FALSE' a list is returned with the following components, 

    perc: a matrix containing the percentages of positive and negative
          responses for each item.

  pw.ass: a matrix containing the p-values for the pairwise association
          between the items.

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

     ## Descriptives for Wirs data:
     descript(Wirs)
     descript(Wirs, 3)
     descript(Wirs, print=FALSE)

