Foreword

Abstract

Random utility models have traditionally been applied to probabilistic choice data, with little attention to reaction times. We describe the class of “horse race” random utility models that can be applied to both choice probabilities and reaction times. We show that any (well bahaved) set of choice probabilities and reaction times on a fixed set can be represented by an independent “horse race” random utility model, and relate this result to work in the theory of competing risks. We use the latter theory to motivate the condition that the option chosen and the time of choice be independent, a condition that is satisfied by a large class of (extreme value) “horse race” random utility models. Combining the latter condition with the assumption of an independent “horse race” random utility model yields a new characterization of Luce's choice model, and a generalization of these conditions to subset choices (as opposed to choosing a single “best” element) yields the transition probabilities of Tversky's elimination-by-aspects model.