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 ...

We then modify the estimating equations of Prentice to estimate the odds ratios. In simulations, the parameter estimates for the logistic regression model for the marginal probabilities appear ...

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 ...

Background: Artificial intelligence (AI)-enhanced electrocardiogram (ECG) models are often designed to detect specific anatomical and functional cardiac abnormalities. Understanding the selectivity of ...

“We performed multivariable logistic regression analysis to define adjusted odds ratios of undergoing PSA testing adjusting for relevant socio-economic and demographic parameters,” the ...

Anxiety and depression following aneurysmal subarachnoid hemorrhage are not significantly associated with socioeconomic status.

Basic logistic regression classification is arguably the most fundamental machine learning (ML) technique. Basic logistic regression can be used for binary classification, for example predicting if a ...

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 ...