Regression and correlation analysis. To understand the factors associated with greater difficulty in performing care coordinator activities, we used multivariable linear regression.

It emphasizes the importance of linear multivariate statistical models, particularly autoregressive (AR) models and the Kalman filter, in time series modeling and prediction of cerebral processes. The ...

Logistic regression can be thought of as an extension to, or a special case of, linear regression. If the outcome variable is a continuous variable, linear regression is more suitable.

Different types of multivariable analysis: generalized linear models Generalized linear models (GLMs, table 2) are a flexible and powerful class of statistical models widely used in multivariable ...

Abstract: In this paper we propose a novel approach for multivariate convex regression by using as approximation model a maximum of hyperplanes, which we represent as a multivariate max-plus tropical ...

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.

Univariate and multivariate linear regression analyses were conducted to determine which variables were related and in which magnitude to PB regression. Baseline PB, baseline unstable core (%), ...