ordROC               package:nonbinROC               R Documentation

_P_e_r_f_o_r_m_s _R_O_C-_t_y_p_e _a_n_a_l_y_s_i_s _f_o_r _o_r_d_i_n_a_l _s_c_a_l_e _g_o_l_d _s_t_a_n_d_a_r_d

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

     Assess the accuracies of diagnostic tests when the gold standard
     is ordinal.

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

     ordROC(gldstd, test1, test2 = NULL, penalty = NULL)

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

  gldstd: vector giving the gold standard

   test1: vector giving the diagnostic test

   test2: optional vector giving the diagnostic test

 penalty: optional square matrix for the penalty function L[i,j] in
          which 0 <= L[i,j] <= 1 for j > i and the remaining elements
          can be set at any value. By default, L[i,j] = 1 for j > i and
          0 otherwise.

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

     In the paired design, `ordROC' returns the pairwise accuracies and
     associated standard errors between  each category of the gold
     standard, the penalty matrix, the overall accuracies and
     associated standard  errors of the diagnostic tests, their overall
     covariance and the test for comparing two diagnostic tests' 
     accuracies. 

     Otherwise, `ordROC' returns the pairwise accuracies and associated
     standard errors between  each category of the gold standard, the
     penalty matrix, the overall accuracy and associated standard 
     error of the diagnostic test.

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

     Paul Nguyen

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

     Obuchowski, N. A. (2005) Estimating and comparing diagnostic
     tests' accuracy when the gold  standard is not binary. _Academic
     Radiology_, 12, 1198-1204.

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

     #An example for heart tissue scarring from Obuchowski (2005)
     data(heart)
     attach(heart)
     penalty = matrix(c(0,0,0,0,0.25,0,0,0,0.5,0.25,0,0,1,0.5,0.25,0), nrow = 4)
     ordROC(PET, MRI, penalty = penalty)

