BEPS                 package:effects                 R Documentation

_B_r_i_t_i_s_h _E_l_e_c_t_i_o_n _P_a_n_e_l _S_t_u_d_y

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

     These data are drawn from the 1997-2001 British Election Panel
     Study (BEPS).

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

     BEPS

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

     A data frame with 1525 observations on the following 10 variables.

     '_v_o_t_e' Party choice: 'Conservative', 'Labour', or 'Liberal
          Democrat'

     '_a_g_e' in years

     '_e_c_o_n_o_m_i_c._c_o_n_d._n_a_t_i_o_n_a_l' Assessment of current national economic
          conditions, 1 to 5.

     '_e_c_o_n_o_m_i_c._c_o_n_d._h_o_u_s_e_h_o_l_d' Assessment of current household economic
          conditions, 1 to 5.

     '_B_l_a_i_r' Assessment of the Labour leader, 1 to 5.

     '_H_a_g_u_e' Assessment of the Conservative leader, 1 to 5.

     '_K_e_n_n_e_d_y' Assessment of the leader of the Liberal Democrats, 1 to
          5.

     '_E_u_r_o_p_e' an 11-point scale that measures respondents' attitudes
          toward European integration. High scores represent
          `Eurosceptic' sentiment.

     '_p_o_l_i_t_i_c_a_l._k_n_o_w_l_e_d_g_e' Knowledge of parties' positions on European
          integration, 0 to 3.

     '_g_e_n_d_e_r' 'female' or 'male'.

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

     J. Fox and R. Andersen (2006) Effect displays  for multinomial and
     proportional-odds logit models. _Sociological Methodology_ *36*,
     225-255.

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

     summary(BEPS)

     require(splines)  # for bs()
     beps <- multinom(vote ~ age + gender + economic.cond.national + economic.cond.household 
             + Blair + Hague + Kennedy + bs(Europe, 3)*political.knowledge, data=BEPS)
     europe.knowledge <- effect("bs(Europe, 3)*political.knowledge", beps, 
             xlevels=list(Europe=seq(1, 11, length=50), political.knowledge=0:3),
             given.values=c(gendermale=0.5))
       
     plot(europe.knowledge)
       
     plot(europe.knowledge, style="stacked", colors=c("blue", "red", "orange"), rug=FALSE)

