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Main Author: Maccallini, Paolo
Format: Recurso digital
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Published: Zenodo 2023
Online Access:https://doi.org/10.5281/zenodo.20177750
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author Maccallini, Paolo
author_facet Maccallini, Paolo
contents <p>This Italian paper proves two key relationships linking multiple linear regression coefficients to simple linear regression coefficients. Working in mean-centered (normalized) coordinates, it shows that the multiple regression slope vector <strong>B</strong> can be expressed as a linear transformation of the simple regression slopes <strong>A</strong> via the matrix (Ξᵀ Ξ)⁻¹Ξ_D, and equivalently that the simple slopes satisfy <strong>A</strong> = Γᵀ<strong>B</strong>, where Γ contains pairwise regression coefficients between the predictors. Variance formulas for both simple and multiple regression estimators are derived, and the paper closes with two reference synopses summarizing standard results for simple and multiple linear regression.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_20177750
institution Zenodo
language
publishDate 2023
publisher Zenodo
record_format zenodo
spellingShingle Sul legame tra i coefficienti di regressione lineare multipla e quelli di regressione lineare semplice
Maccallini, Paolo
<p>This Italian paper proves two key relationships linking multiple linear regression coefficients to simple linear regression coefficients. Working in mean-centered (normalized) coordinates, it shows that the multiple regression slope vector <strong>B</strong> can be expressed as a linear transformation of the simple regression slopes <strong>A</strong> via the matrix (Ξᵀ Ξ)⁻¹Ξ_D, and equivalently that the simple slopes satisfy <strong>A</strong> = Γᵀ<strong>B</strong>, where Γ contains pairwise regression coefficients between the predictors. Variance formulas for both simple and multiple regression estimators are derived, and the paper closes with two reference synopses summarizing standard results for simple and multiple linear regression.</p>
title Sul legame tra i coefficienti di regressione lineare multipla e quelli di regressione lineare semplice
url https://doi.org/10.5281/zenodo.20177750