Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

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

Course Topics"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 ...

Garrett M. Fitzmaurice, Anthony F. Heath, Peter Clifford, Logistic Regression Models for Binary Panel Data with Attrition, Journal of the Royal Statistical Society. Series A (Statistics in Society), ...

The course will end with a brief introduction to regression involving binary response variables (Yes/No or 0/1 outcomes) using logistic regression and count response variables (whole numbers) using ...

The models used are binary logistic regression models based on the full sample of U.S. adults surveyed for this study. The analyses are based on the weighted sample, thus adjusting for differences in ...

Motivated by these problems, we propose a new type of multivariate logistic distribution that can be used to construct a likelihood for multivariate logistic regression analysis of binary and ...

Binomial (or binary) logistic regression analysis is useful for predicting the presence or absence of a characteristic or outcome based on values of a set of predictor variables, and is applicable ...