cslogistic {cslogistic}R Documentation

Perform an Analysis of a conditionally specified logistic regression model

Description

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

Details

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 β j + sum_{k=1, k neq j} αjk yk

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

Author(s)

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

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

References

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.

See Also

MleCslogistic, BayesCslogistic.


[Package cslogistic version 0.1-1 Index]