epiKappa              package:epibasix              R Documentation

_C_o_m_p_u_t_a_t_i_o_n _o_f _t_h_e _K_a_p_p_a _S_t_a_t_i_s_t_i_c _f_o_r _A_g_r_e_e_m_e_n_t _B_e_t_w_e_e_n _T_w_o _R_a_t_e_r_s

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

     Computes the Kappa Statistic for agreement between Two Raters,
     performs Hypothesis tests and calculates Confidence Intervals.

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

     epiKappa(C, alpha=0.05, k0=0.4, digits=3)

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

       C: An nxn classification matrix or matrix of proportions.

      k0: The Null hypothesis, kappa0 = k0

   alpha: The desired Type I Error Rate for Hypothesis Tests and
          Confidence Intervals

  digits: Number of Digits to round calculations

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

     The Kappa statistic is used to measure agreement between two
     raters.  For simplicity, consider the case where each rater can
     classify an object as Type I, or Type II.  Then, the diagonal
     elements of a 2x2 matrix are the agreeing elements, that is where
     both raters classify an object as Type I or Type II.  The
     discordant observations are on the off-diagonal. Note that the
     alternative hypothesis is always greater then, as we are
     interested in whether kappa exceeds a certain threshold, such as
     0.4, for Fair agreement.

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

   kappa: The computation of the kappa statistic.

     seh: The standard error computed under H0

     seC: The standard error as computed for Confidence Intervals

     CIL: Lower Confidence Limit for kappa

     CIU: Upper Confidence Limit for kappa

       Z: Hypothesis Test Statistic, kappa = K0 = K0 vs. kappa > K0

 p.value: P-Value for hypothesis test

    Data: Returns the original matrix of agreement.

      k0: The Null hypothesis, kappa = k0

   alpha: The desired Type I Error Rate for Hypothesis Tests and
          Confidence Intervals

  digits: Number of Digits to round calculations

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

     Michael Rotondi, mrotondi@uwo.ca

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

     Szklo M and Nieto FJ.  Epidemiology: Beyond the Basics, Jones and
     Bartlett: Boston, 2007.

     Fleiss J.  Statistical Methods for Rates and Proportions, 2nd ed. 
     New York: John Wiley and Sons; 1981.

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

     'sensSpec'

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

     X <- cbind(c(28,5), c(4,61));
     summary(epiKappa(X, alpha=0.05, k0 = 0.6));

