Many data professionals regard logistic regression as their preferred statistical method, and for good reason: it is a powerful tool for modeling binary outcomes, with applications across diverse ...

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 ...

"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 data. The most ...

This book also explains the differences and similarities between the many generalizations of the logistic regression model. The following topics are covered: binary logit analysis, logit analysis of ...

The following table details the results of a series of statistical models predicting various measures related to people’s attitudes toward electric. Numbers, Facts and Trends Shaping Your World ...

The observation that Cox proportional hazards models have more statistical power than logistic regression models in association studies has been described previously. 2, 3 For example, the effect ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.