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 ...

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 ...

"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 ...

Microsoft Research's Dr. James McCaffrey show how to perform binary classification with logistic regression using the Microsoft ML.NET code library. The goal of binary classification is to predict a ...

Researchers used 2018 data from the National Health Interview Survey to investigate the association. Men taking anxiety and depression medications were more likely to undergo prostate specific antigen ...

A 29 question-based cross-sectional survey was developed to explore knowledge and practices of predatory publishing and analyzed using descriptive statistics and binary logistic regression. Four ...

Poverty is widespread in the rural areas, where the people are in a state of human deprivation with regard to incomes, clothing, housing, health care, education, sanitary facilities and human rights.