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Assessment of Noninferiority (and Equivalence) for Simple Crossover Trials Using Bayesian Approach

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  • Mingan Yang

    (San Diego State University)

Abstract

To assess the noninferiority or equivalence of a general drug to a standard one, researchers generally use the odds ratio of patient response rates to evaluate the relative treatment efficacy. In this paper, we use a logistic random effects model to test noninferiority and equivalence based on the odds ratio of patient response rates for crossover trials with binary data. We use Bayesian sampling algorithm, data augmentation, and scaled mixture of normal representation to implement the approach and improve efficiency. The performance of the proposed approach is assessed via simulation and real data examples.

Suggested Citation

  • Mingan Yang, 2018. "Assessment of Noninferiority (and Equivalence) for Simple Crossover Trials Using Bayesian Approach," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 506-519, December.
    • Handle: RePEc:spr:stabio:v:10:y:2018:i:3:d:10.1007_s12561-017-9209-9
    DOI: 10.1007/s12561-017-9209-9
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    References listed on IDEAS

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    1. Sean M. O'Brien & David B. Dunson, 2004. "Bayesian Multivariate Logistic Regression," Biometrics, The International Biometric Society, vol. 60(3), pages 739-746, September.
    2. Farkad Ezzet & John Whitehead, 1992. "A Random Effects Model for Binary Data from Crossover Clinical Trials," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(1), pages 117-126, March.
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    Cited by:

    1. Mingan Yang & Min Wang & Guanghui Dong, 2020. "Bayesian variable selection for mixed effects model with shrinkage prior," Computational Statistics, Springer, vol. 35(1), pages 227-243, March.

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