The estimation of random parameters by means of mixed logit models is becoming current practice amongst discrete choice analysts, one of the most straightforward applications being the derivation of willingness to pay distribution over a heterogeneous population. In many practical cases, parametric distributions are a priori specified and the parameters for these distributions are estimated. Th...

— Caussinus’s loglinear model of quasi symmetry has interesting connections with models for within-subject effects with repeated categorical measurement. For binary responses, Tjur (1982) showed that estimates of main effect parameters in the quasi-symmetry model are also conditional maximum likelihood estimates of item parameters for a fixed effects treatment of subject terms in the Rasch item...

This paper investigated factors influencing injury severity of crashes involving median traffic barriers, including the impact barrier characteristics and their geometric features in Wyoming. Combining field data inventoried barriers with crash on Wyoming interstates highways, a random parameters multinomial logit (mixed logit) model was estimated. methodological approach allowed for possibilit...

Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-lognormal random effects model, a two-part logit-truncated normal random effects model, a two-pa...

Elimination by aspects (EBA) is a random utility model that is considered to represent the choice process used by consumers more faithfully than logit and probit models. One limitation of the model is that it does not have a known error theory. We show that EBA can be derived by assuming that aspects have random utilities with independent, extreme value distributions. Multinomial logit and rank...

The random coefficients multinomial choice logit model, also known as the mixed logit, has been widely used in empirical choice analysis for the last thirty years. We prove that the distribution of random coefficients in the multinomial logit model is nonparametrically identified. Our approach requires variation in product characteristics only locally and does not rely on the special regressors...

We develop an extension of the familiar linear mixed logit model to allow for the direct estimation of parametric non-linear functions defined over structural parameters. Classic applications include the estimation of coefficients of utility functions to characterize risk attitudes and discounting functions to characterize impatience. There are several unexpected benefits of this extension, apa...

The effect of risk factors on crash severity varies across vehicle types. objective this study was to explore the associated with rural single-vehicle (SV) crashes. Four types including passenger car, motorcycle, pickup, and truck were considered. To synthetically accommodate unobserved heterogeneity spatial correlation in data, a novel Bayesian random parameters logit (SRP-logit) model is prop...

This paper proposes the use of a quasi-random sequence for the estimation of the mixed multinomial logit model. The mixed multinomial structure is a flexible discrete choice formulation which accommodates general patterns of competitiveness as well as heterogeneity across individuals in sensitivity to exogenous variables. The estimation of this model has been achieved in the past using the pseu...