This article will cover the basic theory behind logistic regression, the types of logistic regression, when to use them and take you through a worked example.

The authors argue that for the cross-sectional multiattribute approach to choice modeling, the multinomial logit is theoretically and empirically superior to the more commonly used regression approach ...

Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies.

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

A logistic regression for these data is a generalized linear model with response equal to the binomial proportion r/n. The probability distribution is binomial, and the link function is logit.

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 ...

Rather than let methodology dictate substantive assumptions, I propose an alternative distribution for the disturbances to the normal or logistic distribution. The resulting estimator developed here, ...