Objective We aimed to estimate prevalence and identify determinants of hypertension in adults aged 15–49 years in Tanzania. Design We analysed cross-sectional survey data from the 2022 Tanzania ...

Separate binary regression models When the dependent variable is ordinal, such as here, we can choose to dichotomise it and use binary logistic regression. A variable with three categories can be ...

Logistic regression is a powerful and versatile tool for modeling binary outcomes, such as yes/no, success/failure, or positive/negative. In this article, you will learn how to use logistic ...

We consider high-dimensional binary classification by sparse logistic regression. We propose a model/feature selection procedure based on penalized maximum likelihood with a complexity penalty on the ...

Sparse logistic regression (SLR), which is widely used for classification and feature selection in many fields, such as neural networks, deep learning, and bioinformatics, is the classical logistic ...

Background Stillbirths and associated outcomes remain a significant concern in sub-Saharan Africa (SSA), with approximately 41% of global stillbirths. Design Our cross-sectional analysis included a ...