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Power of edge exclusion tests for graphical log-linear models

Author

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  • Fátima Salgueiro, M.
  • Smith, Peter W.F.
  • McDonald, John W.

Abstract

Asymptotic multivariate normal approximations to the joint distributions of edge exclusion test statistics for saturated graphical log-linear models, with all variables binary, are derived. Non-signed and signed square-root versions of the likelihood ratio, Wald and score test statistics are considered. Non-central chi-squared approximations are also considered for the non-signed versions of the test statistics. Simulation results are used to assess the quality of the proposed approximations. These approximations are used to estimate the overall power of edge exclusion tests. Power calculations are illustrated using data on university admissions.

Suggested Citation

  • Fátima Salgueiro, M. & Smith, Peter W.F. & McDonald, John W., 2006. "Power of edge exclusion tests for graphical log-linear models," Journal of Multivariate Analysis, Elsevier, vol. 97(8), pages 1691-1701, September.
    • Handle: RePEc:eee:jmvana:v:97:y:2006:i:8:p:1691-1701
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    References listed on IDEAS

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    1. M. Fátima Salgueiro & Peter W. F. Smith & John W. McDonald, 2005. "Power of edge exclusion tests in graphical Gaussian models," Biometrika, Biometrika Trust, vol. 92(1), pages 173-182, March.
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    Cited by:

    1. Christis Katsouris, 2023. "High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods," Papers 2308.16192, arXiv.org.

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