Scott Menard, Six Approaches to Calculating Standardized Logistic Regression Coefficients, The American Statistician, Vol. 58, No. 3 (Aug., 2004), pp. 218-223 ...

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 ...

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

Informal and nontechnical, this book both explains the theory behind logistic regression and looks at all the practical details involved in its implementation using the SAS System. Several social ...

The LOGISTIC and PROBIT procedures can perform logistic and ordinal logistic regression. See Chapter 5, "Introduction to Categorical Data Analysis Procedures," Chapter 39, "The LOGISTIC Procedure," ...

What are the advantages of logistic regression over decision trees? This question was originally answered on Quora by Claudia Perlich.

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you ...