The paper discusses some diagnostic tools for binary logistic regression which use smoothing techniques. Smoothed binary data are employed to devise a battery of diagnostic plots, from simple ...

So, in the case of a binary logistic regression model, the dependent variable is a logit of p, with p being the probability that the dependent variables have a value of 1.

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 ...

A class of conditional logistic regression models for clustered binary data is considered. This includes the polychotomous logistic model of Rosner (1984) as a special case. Properties such as the ...

The Data Science Lab How to Do Logistic Regression Using ML.NET Microsoft Research's Dr. James McCaffrey show how to perform binary classification with logistic regression using the Microsoft ML.NET ...

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population ...