Kappa                  package:vcd                  R Documentation

_C_o_h_e_n'_s _K_a_p_p_a _a_n_d _W_e_i_g_h_t_e_d _K_a_p_p_a

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

     Computes two agreement rates: Cohen's kappa and weighted kappa,
     and confidence bands.

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

     Kappa(x, weights = c("Equal-Spacing", "Fleiss-Cohen"))

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

       x: a confusion matrix.

 weights: either one of the character strings given in the default
          value, or a user-specified matrix with same dimensions as
          'x'.

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

     Cohen's kappa is the diagonal sum of the (possibly weighted)
     relative frequencies, corrected for expected values and
     standardized by its maximum value. The equal-spacing weights are
     defined by 1 - abs(i - j) / (r - 1), r number of colums/rows, and
     the Fleiss-Cohen weights by 1 - abs(i - j)^2 / (r - 1)^2. The
     latter one attaches greater importance to near disagreements.

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

     An object of class '"Kappa"' with three components: 

Unweighted: numeric vector of length 2 with the kappa statistic
          ('value' component), along with Approximate Standard Error
          ('ASE' component)

Weighted: idem for the weighted kappa.

 Weights: numeric matrix with weights used.

_N_o_t_e:

     The 'summary' method also prints the weights.

     There is a 'confint' method for computing approximate confidence
     intervals.

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

     David Meyer David.Meyer@R-project.org

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

     Jacob Cohen (1960), A coefficient of agreement for nominal scales.
     _Educational and Psychological Measurement_, *20*, 37-46.

     B. S. Everitt, (1968), Moments of statistics kappa and weighted
     kappa. _The British Journal of Mathematical and Statistical
     Psychology_, *21*, 97-103.

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

     'agreementplot', 'confint'

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

     data(SexualFun)
     Kappa(SexualFun)

