Properties of Ideal Point Classification Models for Bivariate Binary Data.

The ideal point classification (IPC) model was originally proposed for analysing multinomial data in the presence of predictors. In this paper, we studied properties of the IPC model for analysing bivariate binary data with a specific focus on three quantities: (1) the marginal probabilities; (2) the association structure between the two binary responses; and (3) the joint probabilities. We found that the IPC model with a specific class point configuration represents either the marginal probabilities or the association structure.

A warning concerning the estimation of multinomial logistic models with correlated responses in SAS.

Kuss and McLerran in a paper in this journal provide SAS code for the estimation of multinomial logistic models for correlated data. Their motivation derived from two papers that recommended to estimate such models using a Poisson likelihood, which is according to Kuss and McLerran "statistically correct but computationally inefficient". Kuss and McLerran propose several estimating methods.