Regression models using fractional polynomials of the covariates have appeared in the literature in an ad hoc fashion over a long period; we provide a unified description and a degree of formalization ...

In this paper, we review analytic methods for regression models for longitudinal categorical responses. We focus on both likelihood-based approaches and non-likelihood approaches to analysing repeated ...

Before building my model, I want to step back to offer an easy-to-understand definition of linear regression and why it’s vital to analyzing data. What is linear regression?

This article ( original research paper) proposes a systematic regression-based fundamental equity valuation model that can potentially be applied in areas such as quantitative finance and machine ...

Purpose To collect data for the development of a more universally useful logistic regression model to distinguish between a malignant and benign adnexal tumor before surgery. Patients and Methods ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to see if there's a relationship between two variables, with the first known ...