Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

We propose Bayesian parametric and semiparametric partially linear regression methods to analyze the outcome-dependent follow-up data when the random time of a follow-up measurement of an individual ...

Patients with severe symptomatic aortic stenosis at intermediate and high risk for surgery who, after TAVR, have a larger regression in left ventricular mass at 1 year will then go on to have ...

This is a preview. Log in through your library . Abstract The outcome-dependent sampling scheme has been gaining attention in both the statistical literature and applied fields. Epidemiological and ...

A three-tier tumor regression grading scale effectively predicted risk for distant metastases and DFS after neoadjuvant chemoradiotherapy and total mesorectal excision surgery in patients with rectal ...