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Analysis of Within- and Across-Subject Correlations

  • Sung C. Choi
  • Vernon M. Chinchilli
Part of the Theory and Decision Library book series (TDLB, volume 8)

Abstract

In some fields of applications, response variables are measured on k(k > 1) independent samples for each experimental subject. For this type of situation, within-subject and across-subject correlation matrices are defined and methods of analysis are discussed.

The maximum likelihood estimators for the two different correlation matrices are obtained, and the exact test for within-subject correlation and two approximate tests for across-subject correlation are proposed.

Simulation studies for bivariate distributions suggest that the estimators are satisfactory although the across-subject correlation coefficients are somewhat under estimated. The studies also showed that the two approximate tests are adequate in terms of the size and power. Other properties of the estimators and the tests are discussed.

Key words and phrases

Multivariate Model Within-Subject Correlation Matrix Across-Subject Correlation Matrix Estimation Testing Computer Simulation 

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Copyright information

© D. Reidel Publishing Company, Dordrecht, Holland 1987

Authors and Affiliations

  • Sung C. Choi
    • 1
  • Vernon M. Chinchilli
    • 1
  1. 1.Department of Biostatistics Medical College of VirginiaVirginia Commonwealth UniversityRichmondUSA

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