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.

We used logistic regression as a method of sensitivity analysis for a stochastic population viability analysis model of African wild dogs (Lycaon pictus) and compared these results with conventional ...

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 ...

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.