Impact of 68Ga-PSMA-11 PET/CT on staging and management of prostate cancer patients in various clinical settings. This is an ASCO Meeting Abstract from the 2020 Genitourinary Cancers Symposium. This ...

Single nucleotide polymorphism (SNP) interaction plays a critical role for complex diseases. The primary limitation of logistic regressions (LR) in testing SNP–SNP interactions is that coefficient ...

This paper describes a method for a model-based analysis of clinical safety data called multivariate Bayesian logistic regression (MBLR). Parallel logistic regression models are fit to a set of ...

Understanding the mechanics of adaptive evolution requires not only knowing the quantitative genetic bases of the traits of interest but also obtaining accurate measures of the strengths and modes of ...

To examine the relationship between panic attack and suicide risk, we analyzed data from a representative epidemiological survey of 43,093 adults (NESARC) using logistic regression controlling for ...

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 tool that incorporates five predictors helps accurately identify patients with dermatomyositis who have an increased likelihood of concomitant cancer and can be used to help with early detection.

Before we learn how to perform multivariate regression in Excel, it is important to have a refresher on regression as a whole and multivariate regression in particular. One of the hallmarks of human ...

The study of the pathogenesis of early type 1 diabetes in humans requires long follow-up of a large number of subjects, of which only a small fraction will progress to overt disease, due to the ...