A General Equivalence Theorem for Crossover Designs under Generalized Linear Models

Jeevan Jankar (), Jie Yang () and Abhyuday Mandal ()
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Jeevan Jankar: University of Georgia
Jie Yang: University of Illinois at Chicago
Abhyuday Mandal: University of Georgia

Sankhya B: The Indian Journal of Statistics, 2023, vol. 85, issue 2, No 5, 344-364

Abstract: 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.

Keywords: Approximate design; crossover design; D-optimality; generalized estimating equations; general equivalence theorem; 05B15; 62J12; 62K05; 62L05 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s13571-023-00314-8

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