JSTOR Daily

Integrating the Dirichlet-Multinomial and Multinomial Logit Models of Brand Choice

This paper discusses the interpretative benefits that arise from merging the Dirichlet- multinomial (DM) model as a loyalty variable in the multinomial logit (MNL) model of brand choice. The estimated ...
Scientific Research Publishing

Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity ()

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...
JSTOR Daily

Controlling for overdispersion in grouped conditional logit models: A computationally simple application of Dirichlet-multinomial regression

In this article, we provide a random utility-based derivation of the Dirichlet-multinomial regression and propose it as a convenient alternative for dealing with overdispersed multinomial data. We ...
Kellogg School of Management

A Practitioner's Guide to Estimation of Random-Coefficients Logit Models of Demand

Citations: Nevo, Aviv. 2000. A Practitioner's Guide to Estimation of Random-Coefficients Logit Models of Demand. Journal of Economics & Management Strategy. (4)513-548.
technologynetworks

Logistic Regression

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...