cautres                 package:gnm                 R Documentation

_D_a_t_a _o_n _C_l_a_s_s, _R_e_l_i_g_i_o_n _a_n_d _V_o_t_e _i_n _F_r_a_n_c_e

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

     A 4-way contingency table of vote by class by religion in four
     French elections

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

     data(cautres)

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

     A table of counts, with classifying factors 'vote' (levels '1:2'),
     'class' (levels '1:6') and 'religion' (levels '1:4') and
     'election' (levels '1:4').

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

     Bruno Cautres

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

     Cautres, B, Heath, A F and Firth, D (1998).  Class, religion and
     vote in Britain and France.  _La Lettre de la Maison Francaise_
     *8*.

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

     set.seed(1)
     data(cautres)

     ##  Fit a "double UNIDIFF" model with the religion-vote and class-vote
     ##  interactions both modulated by nonnegative election-specific multipliers
     doubleUnidiff <- gnm(Freq ~ election:vote + election:class:religion +
                          Mult(Exp(-1 + election), religion:vote) +
                          Mult(Exp(-1 + election), class:vote),
                          family = poisson, data = cautres)
     ##  Deviance should be 133.04

     ##  Examine the multipliers of the class-vote log odds ratios
     coefs.of.interest <- grep("Mult2.*election", names(coef(doubleUnidiff)))
     coef(doubleUnidiff)[coefs.of.interest]
     ##  Mult2.Factor1.election1 Mult2.Factor1.election2 
     ##               -0.5724370               0.1092972 
     ##  Mult2.Factor1.election3 Mult2.Factor1.election4 
     ##               -0.1230682              -0.2105843
     getContrasts(doubleUnidiff, coefs.of.interest)
     ##                            estimate        se
     ##  Mult2.Factor1.election1 -0.3618399 0.2534762
     ##  Mult2.Factor1.election2  0.3198951 0.1320034
     ##  Mult2.Factor1.election3  0.0875308 0.1446842
     ##  Mult2.Factor1.election4  0.0000000 0.0000000

     ##  Same thing but with election 1 as reference category:
     getContrasts(doubleUnidiff, rev(coefs.of.interest))
     ##                            estimate        se
     ##  Mult2.Factor1.election4  0.3618399 0.2534746
     ##  Mult2.Factor1.election3  0.4493707 0.2473524
     ##  Mult2.Factor1.election2  0.6817351 0.2401645
     ##  Mult2.Factor1.election1  0.0000000 0.0000000

