EIGHT. Principles in Dealing with Correlated Data

  1. Mari Palta

Published Online: 11 AUG 2003

DOI: 10.1002/0471467979.ch8

Quantitative Methods in Population Health: Extensions of Ordinary Regression

Quantitative Methods in Population Health: Extensions of Ordinary Regression

How to Cite

Palta, M. (2003) Principles in Dealing with Correlated Data, in Quantitative Methods in Population Health: Extensions of Ordinary Regression, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/0471467979.ch8

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:

  • correlated data;
  • longitudinal data;
  • spectral theorem;
  • compound symmetry;
  • unstructured covariance;
  • block diagonal;
  • empirical variance;
  • principal components;
  • information criterion;
  • REPEATED statement

Summary

We provide examples of situations with correlated data. Unbiasedness of ordinary least squares estimators. Block diagonal variance matrices and how block diagonality simplifies matrix operations. Empirical variance with block diagonal structure. The spectral theorem and its application to correlated data and in principal components analysis. Different correlation structures are introduced. Applying correlation structures in analyses with PROC MIXED are shown and criteria discussed for choosing the best model.

Multivariate normal distribution. Maximum likelihood analysis of correlated data. Analysis of longitudinal blood pressure data with different assumptions on the correlation structure.