The multinomial logit model is perhaps the most commonly used regression model for nominal outcomes in the social sciences. A concern raised by many researchers, however, is the assumption of the independence of irrelevant alternatives (IIA) that is implicit in the model. In this article, the authors undertake a series of Monte Carlo simulations to evaluate the three most commonly discussed tes...

The generalized nested logit model is a new member of the generalized extreme value family of models. The GNL provides a higher degree of flexibility in the estimation of substitution or cross-elasticity between pairs of alternatives than previously developed generalized extreme value models. The generalized nested logit model includes the paired combinatorial logit and cross-nested logit model...

The multinomial logit model is the most widely used model for nominal multi-category responses. One problem with the model is that many parameters are involved, another that interpretation of parameters is much harder than for linear models because the model is non-linear. Both problems can profit from graphical representations. We propose to visualize the effect strengths by star plots, where ...

The familiar logit and probit models provide convenient settings for many binary response applications, but a larger class of link functions may be occasionally desirable. Two parametric families of link functions are investigated: the Gosset link based on the Student t latent variable model with the degrees of freedom parameter controlling the tail behavior, and the Pregibon link based on the ...

While providing the resources and tools that make advanced research possible is a primary mission of academic libraries at large research universities, many other elements also contribute to the success of the research enterprise, such as institutional funding, staffing, labs, and equipment. This study focuses on U.S. members of the Association for Research Libraries (ARL). Research success is ...

With samples from Akure Nigeria, the study examined the variation of the satisfaction of the people living around GSM base stations with distance away from the location of the base station. Using Crosstabs' nominal-by-nominal measures, the study found that the further the distances away from the base station, the higher the percentages of those that are satisfied; When the effect of fear of hea...

This paper discusses the representability of discrete logit-type models including multinomial logit and nested logit model from a mathematical approach. It is shown that the logit-type models can be reconstructed from mathematical approximation theory with sigmoidal functions widely used in Neural Network modeling without the basic assumptions such as IIA and iid, and the distribution (or densi...

Weight of evidence (WOE) coding of a nominal or discrete variable is widely used when preparing predictors for usage in binary logistic regression models. When using WOE coding, an important preliminary step is binning of the levels of the predictor to achieve parsimony without giving up predictive power. These concepts of WOE and binning are extended to ordinal logistic regression in the case ...

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...