wkappa                  package:psy                  R Documentation

_w_e_i_g_h_t_e_d _K_a_p_p_a _f_o_r _2 _r_a_t_e_r_s

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

     Computes a weighted Kappa for agreement in the case of 2 raters.
     The diagnosis (the object of the rating) may have k possible
     ordered values.

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

     wkappa(r,weights="squared")

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

       r: n*2 matrix or dataframe, n subjects and 2 raters

 weights: weights="squared" to obtain squared weights. If not, absolute
          weights are computed (see details)

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

     The diagnoses are ordered as follow: numbers < letters, letters
     and numbers ordered naturally. For weigths="squared", weights are
     related to squared differences between rows and columns indices
     (in this situation wkappa is close to an icc). For
     weights!="squared", weights are related to absolute values of
     differences between rows and columns indices. The function deals
     with the case where the two raters have not exactly the same scope
     of rating (some software associate an error with this situation).
     Missing value are omitted.

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

     A list with : 

  $table: the 2*k table of raw data (first rater in rows, second rater
          in columns)

$weights: "squared" or "absolute"

  $kappa: Weighted Kappa

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

     Bruno Falissard

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

     Cohen, J. Weighted kappa: nominal scale agreement with provision
     for scaled disagreement or partial credit. Psychological Bulletin
     70 (1968): 213-220.

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

     data(expsy)
     wkappa(expsy[,c(11,13)])        # weighted kappa (squared weights)

     library(boot)
     wkappa.boot <- function(data,x) {wkappa(data[x,])[[3]]}
     res <- boot(expsy[,c(11,13)],wkappa.boot,1000)
     quantile(res$t,c(0.025,0.975))  # two-sided bootstrapped confidence interval of weighted kappa

