For binary logistic regression, dependent variables must be binary, while ordinal logistic regression requires ordinal dependent variables—variables that occur in natural, ordered categories.

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Course Topics"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 ...

A new global test statistic for models with continuous covariates and binary response is introduced. The test statistic is based on nonparametric kernel methods.

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.

Recent studies indicate that these approximate solutions exhibit considerable bias and provide little advantage over use of traditional logistic regression analysis ignoring the hierarchical structure ...