Conditional parameter estimates from mixed logit models: Distributional assumptions and a free software tool - Stephane Hess (Journal of Choice Modelling, 2010)
A number of authors have discussed the possible advantages of conditioning parameter distributions on observed choices when working with Mixed Multinomial Logit models. However, the number of applications is still relatively small, partly due to a limited implementation in available software. To address this situation, the present paper discusses the development of a freeware software tool that allows users to compute conditional distributions independently of the software used during model estimation. Additionally, the paper looks at what impact assumptions made for the unconditional distributions have on the results obtained with conditional distributions. Here, an application using stated choice data collected in Denmark shows that while the move from unconditional to conditional distributions possibly brings results closer together, some discrepancies do remain.
Keywords: 330; mixed logit; discrete choice; conditional distributions; taste heterogeneity