mammoexp                package:party                R Documentation

_M_a_m_m_o_g_r_a_p_h_y _E_x_p_e_r_i_e_n_c_e _S_t_u_d_y

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

     Data from a questionaire on the benefits of mammography.

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

     data(mammoexp)

_F_o_r_m_a_t:

     A data frame with 412 observations on the following 6 variables.

     _M_E Mammograph experience, an ordered factor with  levels 'Never' <
          'Within a Year' < 'Over a Year'

     _S_Y_M_P_T Agreement with the statement:  `You do not need a mamogram
          unless you develop symptoms.'  A factor with levels 'Strongly
          Agree', 'Agree', 'Disagree' and 'Strongly Disagree'

     _P_B Perceived benefit of mammography, the sum of five scaled
          responses, each on a four point scale. A low value is
          indicative of a woman with strong agreement  with the
          benefits of mammography.

     _H_I_S_T Mother or Sister with a history  of breast cancer; a factor
          with levels 'No' and 'Yes'.

     _B_S_E Answers to the question:  `Has anyone taught you how to
          examine your own breasts?' A factor with levels 'No' and
          'Yes'. 

     _D_E_C_T Answers to the question:  `How likely is it that a mammogram
          could find a new case of breast cancer?' An ordered factor
          with levels 'Not likely' <  'Somewhat likely' < 'Very
          likely'.

_S_o_u_r_c_e:

     Hosmer and Lemeshow (2000). _Applied Logistic Regression_, 2nd
     edition. John Wiley & Sons Inc., New York. Section 8.1.2, page
     264.

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

       ### fit tree with attached scores (but those are the default values anyway)
       ctree(ME ~ .,data = mammoexp, 
             scores = list(ME = 1:3, SYMPT = 1:4, DECT = 1:3))

