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

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.

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.

Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

A logistic regression model for characterizing differential item functioning (DIF) between two groups is presented. A distinction is drawn between uniform and nonuniform DIF in terms of the parameters ...

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.