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A Note on Transition Models for Binary 2×2 Cross-Over Data

Author

Listed:
  • Kurosawa T

    (Department of Applied Mathematics, Tokyo University of Science, Japan)

  • Shimokawa A

    (Department of Mathematics, Tokyo University of Science, Japan)

  • Miyaoka E

    (Department of Mathematics, Tokyo University of Science, Japan)

Abstract

This paper presents a transition model within the framework of a generalized linear model for binary cross-over data. As a simple example, an analysis of binary 2×2 cross-over data on cerebrovascular deficiency is used to illustrate the model. Several simulation studies are carried out to assess the asymptotic properties of the estimators of the parameters included in the model, with finite sample size, and to compare common methods with respect to the hypothesis test corresponding to the treatment effect. As a main result, we show that the estimators’ asymptotic properties work with a moderate sample size, and the transition model takes the highest value with respect to the empirical power among the compared methods.

Suggested Citation

  • Kurosawa T & Shimokawa A & Miyaoka E, 2017. "A Note on Transition Models for Binary 2×2 Cross-Over Data," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 3(5), pages 141-146, October.
    • Handle: RePEc:adp:jbboaj:v:3:y:2017:i:5:p:141-146
    DOI: 10.19080/BBOAJ.2017.03.555622
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    References listed on IDEAS

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    1. Fokianos, Konstantinos & Kedem, Benjamin, 1998. "Prediction and Classification of Non-stationary Categorical Time Series," Journal of Multivariate Analysis, Elsevier, vol. 67(2), pages 277-296, November.
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