Mixed Logit Model on Multivariate Binary Response using Maximum Likelihood Estimator and Generalized Estimating Equations

This study presents discussion on the effects of correlation among response respect to estimator properties in mixed logit model on multivariate binary response. It is assumed that each respondent was observed for T response. Yit is the tth response for the ith individual/subject and each response is binary. Each subject has covariate Xi (individual characteristic) and covariate Zijt (characteristic of alternative j). Individual response i that is represented by Yi = (Yi1,....,YiT), Yit is tnd response on ith individual/subject and the response is binary. In order to simplify, one of individual characteristic was and alternative characteristics. We studied effects of correlations using data simulation. Methods of estimations used in this study are Generalized Estimating Equations (GEE) and Maximum Likelihood Estimator (MLE). We generate data and estimate parameters using software R.2.10. From simulation data, we conclude that MLE on mixed logit model is better than GEE. The higher correlation among utility, the higher deviation estimator to parameter.