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A General Equivalence Theorem for Crossover Designs under Generalized Linear Models

Author

Listed:
  • Jeevan Jankar

    (University of Georgia)

  • Jie Yang

    (University of Illinois at Chicago)

  • Abhyuday Mandal

    (University of Georgia)

Abstract

With the help of Generalized Estimating Equations, we identify locally D-optimal crossover designs for generalized linear models. We adopt the variance of parameters of interest as the objective function, which is minimized using constrained optimization to obtain optimal crossover designs. In this case, the traditional general equivalence theorem could not be used directly to check the optimality of obtained designs. In this manuscript, we derive a corresponding general equivalence theorem for crossover designs under generalized linear models.

Suggested Citation

  • Jeevan Jankar & Jie Yang & Abhyuday Mandal, 2023. "A General Equivalence Theorem for Crossover Designs under Generalized Linear Models," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(2), pages 344-364, November.
    • Handle: RePEc:spr:sankhb:v:85:y:2023:i:2:d:10.1007_s13571-023-00314-8
    DOI: 10.1007/s13571-023-00314-8
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    References listed on IDEAS

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    1. R. A. Bailey & J. Kunert, 2006. "On optimal crossover designs when carryover effects are proportional to direct effects," Biometrika, Biometrika Trust, vol. 93(3), pages 613-625, September.
    2. Jegar Pitchforth & Elizabeth Nelson-White & Marc van den Helder & Wouter Oosting, 2020. "The work environment pilot: An experiment to determine the optimal office design for a technology company," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-33, May.
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