As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...

It is well known that the maximum likelihood fit of the logistic regression parameters can be greatly affected by atypical observations. Several robust alternatives have been proposed. However, if we ...

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 ...

This article introduces a new type of logistic regression model involving functional predictors of binary responses, and provides an extension of this approach to generalized linear models. The ...

The faecal immunochemical test (FIT) is replacing the guaiac faecal occult blood test in colorectal cancer screening. Increased uptake and FIT positivity will challenge colonoscopy services. We ...

The fundamental technique has been studied for decades, thus creating a huge amount of information and alternate variations that make it hard to tell what is key vs. non-essential information.

We trained models using logistic regression (LR) and four commonly used ML algorithms to predict NCGC from age-/sex-matched controls in two EHR systems: Stanford University and the University of ...

Multicenter Phase I/II Study of Cetuximab With Paclitaxel and Carboplatin in Untreated Patients With Stage IV Non–Small-Cell Lung Cancer Data from 1,066 patients recruited from nine European centers ...