Chapter THREE. Reformulating Ordinary Regression Analysis in Matrix Notation
Published Online: 11 AUG 2003
DOI: 10.1002/0471467979.ch3
Copyright © 2003 John Wiley & Sons, Inc.
Book Title
Quantitative Methods in Population Health: Extensions of Ordinary Regression
Additional Information
How to Cite
Palta, M. (2003) Reformulating Ordinary Regression Analysis in Matrix Notation, in Quantitative Methods in Population Health: Extensions of Ordinary Regression, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471467979.ch3
Publication History
- Published Online: 11 AUG 2003
- Published Print: 15 AUG 2003
Book Series:
Book Series Editors:
- Walter A. Shewhart,
- Samuel S. Wilks
ISBN Information
Print ISBN: 9780471455059
Online ISBN: 9780471467977
- Summary
- Chapter
Keywords:
- matrices;
- least squares;
- unbiasedness;
- matrix notation;
- matrix rules;
- matrix formulation
Summary
We motivate the need for matrix notation for writing regression equations and estimators with multiple predictors. Ordinary regression equation is rewritten in matrix notation. Least squares equations are rewritten in matrix notation. Unbiasedness of least squares estimators is demonstrated. An example with matrices is generated by PROC REG ALL option. A basic list of matrix operations and equalities is provided. Matrix operations are illustrated for regression of systolic blood pressure on age.