cslogistic            package:cslogistic            R Documentation

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

     This package contains functions for likelihood and posterior
     analysis of conditionally specified logistic regression models.

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

     Assume that for each of n experimental units the values of m
     binary variables 

                            Yi1, ..., Yim

     are recorded. The 'MleCslogistic' and 'BayesCslogistic' functions
     fit a  conditional specified logistic regression model, such that
     for i = 1, ..., n  and j = 1, ..., m,


 logit P(Yij=1 | Yik=yk, k neq j) = Xij beta j + sum_{k=1, k neq j} alphajk yk


     where, the parameters alphajk have interpretation as conditional
     log-odds ratios and  the parameters beta j correspond to the
     regression coefficients associated to the vector of  covariates
     Xij. For compatibility of conditional distributions it is assumed
     that  alphajk = alphakj, j neq k .

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

     Alejandro Jara Vallejos Alejandro.JaraVallejos@med.kuleuven.be

     Maria Jose Garcia-Zattera MariaJose.GarciaZattera@med.kuleuven.be

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

     Garcia-Zattera, M. J., Jara, A., Lesaffre, E. and Declerck, D.
     (2005). On conditional  independence for multivariate binary data
     in caries research. In preparation.

     Joe, H. and Liu, Y. (1996). A model for multivariate response with
     covariates based on  compatible conditionally specified logistic
     regressions. Satistics & Probability Letters  31: 113-120.

_S_e_e _A_l_s_o:

     'MleCslogistic', 'BayesCslogistic'.

