In this article, we extend the discussion of prediction models of Configural Frequency Analysis (CFA). We build on the correspondence of such prediction models to logit models that was shown by von Eye and Bogat (in this issue), and derive additional possible CFA prediction models. These models can, as is illustrated, include multiple predictors and multiple criteria. Design matrices are presen...

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...

Categorical outcome (or discrete outcome or qualitative response) regression models are models for a discrete dependent variable recording in which of two or more categories an outcome of interest lies. For binary data (two categories) probit and logit models or semiparametric methods are used. For multinomial data (more than two categories) that are unordered, common models are multinomial and...

The Multinomial Logit, discrete choice model of transport demand, has several restrictions when compared with the more general Multinomial Probit model. The most famous of these are that unobservable components of utilities should be mutually independent and homoskedastic. Correlation can be accommodated to a certain extent by the Hierarchical Logit model, but the problem of heteroskedasticity ...

The current note summarizes the findings of our nested Logit analysis of the use of health care services in Cameroon. The objectives of that analysis were: (i) identify the determinants of the choice of health care providers in Cameroon, and (ii) determine the compensation to the poor to get them away from traditional/self healing. For that purpose a nested Logit model was built to account for ...

This paper focuses on the relevance of alternate discrete outcome frameworks for modeling driver injury severity. The study empirically compares the ordered response and unordered response models in the context of driver injury severity in traffic crashes. The alternative modeling approaches considered for the comparison exercise include: for the ordered response framework-ordered logit (OL), g...

Logit dynamics [Blume, Games and Economic Behavior, 1993] is a randomized best response dynamics where at every time step a player is selected uniformly at random and she chooses a new strategy according to the “logit choice function”, i.e. a probability distribution biased towards strategies promising higher payoffs, where the bias level corresponds to the degree of rationality of the agents. ...

The nested logit model has been widely used to study nested choice. A typical example of such nested choice is store patronage and brand choice. An important limitation of the nested logit model is that it assumes that all alternatives at both levels of the nest are available in the choice set of the consumer. While there is a wide literature on the incorporation of restricted choice sets into ...

Logit dynamics are a family of randomized best response dynamics based on the logit choice function [21] that is used to model players with limited rationality and knowledge. In this paper we study the all-logit dynamics, where at each time step all players concurrently update their strategies according to the logit choice function. In the well studied one-logit dynamics [7] instead at each ste...