Chapter TWO. The Maximum Likelihood Approach to Ordinary Regression
Published Online: 11 AUG 2003
DOI: 10.1002/0471467979.ch2
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) The Maximum Likelihood Approach to Ordinary Regression, in Quantitative Methods in Population Health: Extensions of Ordinary Regression, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471467979.ch2
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:
- maximum likelihood;
- density;
- normal distribution;
- consistency;
- efficiency;
- invariance;
- PROC MIXED;
- ML;
- REML;
- bias
Summary
We introduce the likelihood idea for binary outcome. The concept of density is introduced for continuous outcome, and the formula for the normal density is provided. The likelihood is maximized using derivatives for ordinary regression analysis with normality assumption on the error term. Important properties of maximum likelihood are defined, PROC MIXED is introduced. Systolic blood pressure is regressed on age.