TWO. The Maximum Likelihood Approach to Ordinary Regression

  1. Mari Palta

Published Online: 11 AUG 2003

DOI: 10.1002/0471467979.ch2

Quantitative Methods in Population Health: Extensions of Ordinary Regression

Quantitative Methods in Population Health: Extensions of Ordinary Regression

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

Author Information

  1. Madison, Wisconsin, USA

Publication History

  1. Published Online: 11 AUG 2003
  2. Published Print: 15 AUG 2003

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780471455059

Online ISBN: 9780471467977

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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.