vif                   package:car                   R Documentation

_V_a_r_i_a_n_c_e _I_n_f_l_a_t_i_o_n _F_a_c_t_o_r_s

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

     Calculates variance-inflation and generalized variance-inflation
     factors for linear models.

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

     vif(mod)

     ## S3 method for class 'lm':
     vif(mod)

     ## Default S3 method:
     vif(mod)

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

     mod: an unweighted 'lm' object.

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

     If all terms in the model have 1 df, then the usual
     variance-inflation factors are calculated.

     If any terms have more than 1 df, then generalized
     variance-inflation factors (Fox and Monette, 1992) are calculated.
     These are interpretable as the inflation in size of the confidence
     ellipse or ellipsoid for the coefficients of the term in
     comparison with what would be obtained for orthogonal data. 

     The generalized vifs are invariant with respect to the coding of
     the terms in the model (as long as the subspace of the columns of
     the model matrix pertaining to each term is invariant). To adjust
     for the dimension of the confidence ellipsoid, the function also
     prints GVIF^{1/(2times df)}.

     Currently, 'vif' is only defined for linear models; 'vif.default'
     is a dummy function that generates an error.

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

     A vector of vifs, or a matrix containing one row for each term in
     the model, and columns for the GVIF, df, and GVIF^{1/(2times df)}.

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

     John Fox jfox@mcmaster.ca

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

     Fox, J. and Monette, G. (1992) Generalized collinearity
     diagnostics. _JASA_, *87*, 178-183.

     Fox, J. (1997) _Applied Regression, Linear Models, and Related
     Methods._ Sage.

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

     data(Duncan)
     vif(lm(prestige~income+education, data=Duncan))
     ##    income education 
     ##  2.104900  2.104900 
     vif(lm(prestige~income+education+type, data=Duncan))
     ##               GVIF Df GVIF^(1/2Df)
     ## income    2.209178  1     1.486330
     ## education 5.297584  1     2.301648
     ## type      5.098592  2     1.502666

