This paper proposes a new spatial multivariate count model to jointly analyze the traffic crash- related counts of pedestrians and bicyclists by injury severity. The modeling framework is applied to predict injury counts ...

In the context of panel ordered-response structures, the current paper compares the performance of the maximum-simulated likelihood (MSL) inference approach and the composite marginal likelihood (CML) inference approach. ...

The current paper proposes an approach to accommodate flexible spatial dependency structures in discrete choice models in general, and in unordered multinomial choice models in particular. The approach is applied to ...

The likelihood functions of multinomial probit (MNP)-based choice models entail the evaluation of analytically-intractable integrals. As a result, such models are usually estimated using maximum simulated likelihood (MSL) ...

This paper evaluates the ability of the maximum approximate composite marginal likelihood (MACML) estimation approach to recover parameters from finite samples in mixed cross-sectional and panel multinomial probit models. ...

This paper proposes a flexible econometric structure for injury severity analysis at the level of individual crashes that recognizes the ordinal nature of injury severity categories, allows unobserved heterogeneity in ...

This paper proposes a reformulation of count models as a special case of generalized orderedresponse models in which a single latent continuous variable is partitioned into mutually exclusive intervals. Using this ...

Recent research suggests that, besides traditional socio-demographic and built environment attributes, the attitudes and perceptions of parents towards walking and bicycling play a crucial role in deciding their children’s ...

This paper presents a joint model of walking and bicycling activity duration using a hazard based specification that recognizes the interval nature of time reported in activity-travel surveys. The model structure takes the ...

The focus of this paper is to develop a procedure for the Maximum Composite Marginal Likelihood (MACML) estimation of multinomial logit models with normally mixed terms, as would be the case with normally-mixed random ...