JSTOR Daily

A Graphical Tool for Interpreting Regression Coefficients of Trinomial Logit Models

Multinomial logit (also termed multi-logit) models permit the analysis of the statistical relation between a categorical response variable and a set of explicative variables (called covahates or ...
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 ...
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 ...
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.
CU Boulder News & Events

Regression for Binary and Count Data: Logistic and Poisson Regression

"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count data. The most ...