Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

A pre-planned secondary analysis was performed in which the primary outcome was the dependent variable and treatment allocation, centre, type of surgery and age were included as covariates in a ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

Background Immune-mediated processes leading to childhood type 1 diabetes may begin in fetal life. We hypothesised that a ...

Objective Long-term azithromycin treatment effectively prevents acute exacerbations of chronic obstructive pulmonary disease (COPD). However, patients would benefit from better identification of ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

Linear regression, a fundamental statistical method, serves as the backbone for predictive modeling in various fields. Whether you're a data scientist, analyst, or just someone curious about making ...

This paper critically examines ‘kitchen sink regression’, a practice characterised by the manual or automated selection of variables for a multivariable regression model based on p values or ...

FLORAL: Fit LOg-RAtio Lasso regression for compositional covariates The FLORAL package is an open-source computational tool to perform log-ratio lasso regression modeling and compositional feature ...