In a logistic regression model, the coefficients (represented by β in the equation) represent the log odds of the outcome variable being 1 for each one-unit increase in a particular explanatory ...

Peiming Wang, Martin L. Puterman, Mixed Logistic Regression Models, Journal of Agricultural, Biological, and Environmental Statistics, Vol. 3, No. 2 (Jun., 1998), pp ...

In these kinds of situations, we would prefer a model that is easy to interpret, such as the logistic regression model. The Delta-p statistics makes the interpretation of the coefficients even easier.

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

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity.

The log-logistic distribution has a non-monotonic hazard function which makes it suitable for modelling some sets of cancer survival data. A log-logistic regression model is described in which the ...