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Multiple Hypotheses in the Analysis of a Crossover Trial

Author

Listed:
  • Yi Hao

    (Rutgers U. Department of Statistics and Biostatistics)

  • John Kolassa

    (Rutgers U. Department of Statistics and Biostatistics)

Abstract

Crossover trials are used in a variety of fields, such as medicine, biology, psychology, and some commercial goods investigations. The aim of this paper is to extend a methodology for multiple comparisons to the problem of testing in crossover trials with two treatments. These two treatments are given in two orderings, treatment A first or treatment B first. We perform inference on the effect of one treatment relative to the effect of the other, without assuming that these effects are independent of treatment ordering, using techniques from order-restricted inference and multiple comparisons, and compare to some existing multiple comparison tests.

Suggested Citation

  • Yi Hao & John Kolassa, 2016. "Multiple Hypotheses in the Analysis of a Crossover Trial," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 253-263, October.
    • Handle: RePEc:spr:stabio:v:8:y:2016:i:2:d:10.1007_s12561-016-9142-3
    DOI: 10.1007/s12561-016-9142-3
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    References listed on IDEAS

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    1. Alexander Shapiro & Jos Berge, 2002. "Statistical inference of minimum rank factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 67(1), pages 79-94, March.
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