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Testing of a Structures Covariance Matrix for Three-Level Repeated Measures Data

Author

Listed:
  • Anuradha Roy

    (The University of Texas at San Antonio)

  • Ricardo Leiva

    (F.C.E., Universidad Nacional de Cuyo)

Abstract

This paper considers the problem of estimating, and testing for, a Kronecker product covariance structure of three-level (multiple time points (p), multiple sites (u), and multiple response variables (q)) multivariate data. Testing of such covariance structures is potentially important when not enough samples are available to estimate the unstructures variance-covariance matrix. This hypothesis procedure not only can test the hypothesis on three-level multivariate data, but also can test the hypotheses on two-level multivariate data as special cases. We provide the maximum likelihood estimates of the unknown population parameters. The test is implemented with a real data set.

Suggested Citation

  • Anuradha Roy & Ricardo Leiva, 2008. "Testing of a Structures Covariance Matrix for Three-Level Repeated Measures Data," Working Papers 0037, College of Business, University of Texas at San Antonio.
    • Handle: RePEc:tsa:wpaper:0082mss
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    References listed on IDEAS

    as
    1. Justine Shults & Ardythe L. Morrow, 2002. "Use of Quasi–Least Squares to Adjust for Two Levels of Correlation," Biometrics, The International Biometric Society, vol. 58(3), pages 521-530, September.
    2. Leiva, Ricardo, 2007. "Linear discrimination with equicorrelated training vectors," Journal of Multivariate Analysis, Elsevier, vol. 98(2), pages 384-409, February.
    3. Lu, Nelson & Zimmerman, Dale L., 2005. "The likelihood ratio test for a separable covariance matrix," Statistics & Probability Letters, Elsevier, vol. 73(4), pages 449-457, July.
    4. Dayanand Naik & Shantha Rao, 2001. "Analysis of multivariate repeated measures data with a Kronecker product structured covariance matrix," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(1), pages 91-105.
    5. Ritter, Gunter & Gallegos, María Teresa, 2002. "Bayesian Object Identification: Variants," Journal of Multivariate Analysis, Elsevier, vol. 81(2), pages 301-334, May.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Kronecker product covariance structure; maximum likelihood estimates; equicorrelated partitioned matrix; three-level multivariate data.;
    All these keywords.

    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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