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 ...

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 ...

I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems. Logistic regression is a technique used to make ...

"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 ...

This is a preview. Log in through your library . Abstract Longitudinal studies of a binary outcome are common in the health, social, and behavioral sciences. In general, a feature of random effects ...