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 regression is a technique used to make predictions in situations where the item to predict can take one of just two possible values. For example, you might want to predict the credit ...

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 ...

Two logistic regression frameworks were adopted for comparison. One was the logit function provided in the Python-based statsmodels module and referred to as “sm.logit.” ...

Parametric empirical Bayes methods are discussed for estimating the mean proportion response from generalized linear regression models (GLiM's) based on the binomial distribution, including the ...

Linda June Davis, Modification of the Empirical Logit to Reduce Bias in Simple Linear Logistic Regression, Biometrika, Vol. 72, No. 1 (Apr., 1985), pp. 199-202 ...