An important goal in clinical and statistical research is properly modeling the distribution for clustered failure times which have a natural intraclass dependency and are subject to censoring. We handle these challenges with a novel approach that does not impose restrictive modeling or distributional assumptions. Using a logit transformation, we relate the distribution for clustered failure ti...

This paper investigates the application of a nested logit model to urban transit networks where every set of competitive transit lines is described by a particular graph structure called hyperpath. It shows that the nested logit model transcends the inherent limitations of the simple logit model while retaining the algorithmic advantages similar to that obtained with the ordinary logit model fo...

The multinomial logit model with random eeects is often used in modeling correlated nominal polytomous data. Given that there is no standard software of tting it, we advocate using either a Poisson log-linear model or a Poisson nonlinear model, both with random eeects. Their implementations can be carried out easily by many existing commercial statistical packages including SAS. A brand choice ...

The random parameters logit model for aggregate data introduced by Berry, Levinsohn, and Pakes (1995) has been a driving force in empirical industrial organization for more than a decade. While these models are identified in theory, identification problems often occur in practice. In this paper we introduce a new set of readily available instruments that have the potential to substantially impr...

This is a short overview of the R add-on package BradleyTerry2, which facilitates the specification and fitting of Bradley-Terry logit, probit or cauchit models to paircomparison data. Included are the standard ‘unstructured’ Bradley-Terry model, structured versions in which the parameters are related through a linear predictor to explanatory variables, and the possibility of an order or ‘home ...

This research investigates the factors that lead to three manners of collision (namely, rear-end, angle, and sideswipe) that occurred in the same direction of multilane interstate highways. Mixed logit (MXL) models were developed to estimate the probability of rear-end, angle, and sideswipe collisions as functions of vehicle-following attributes and other driving maneuvers immediately before co...

There is a growing recognition that discrete choice models are capable of providing a more realistic picture of route choice behavior. In particular, influential factors other than travel time that are found to affect the choice of route trigger the application of random utility models in the route choice literature. This paper focuses on path-based, logit-type stochastic route choice models, i...

Random utility models are widely used to estimate preference parameters. In the case of intertemporal choice, two most common discounted logit and one we call Luce. Due their apparent similarity, choice use model or other seems irrelevant. this paper, argue that Luce is superior in significant aspects. First, relevant applications, monotone sense Apesteguia Ballester (2018), while not. Second, ...