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Multiple Statistical Inferences

In: Statistics Applied to Clinical Trials

Author

Listed:
  • Ton J. Cleophas

    (European Interuniversity College of Pharmaceutical Medicine Lyon
    Albert Schweitzer Hospital, Department Medicine)

  • Aeilko H. Zwinderman

    (Academic Medical Center Amsterdam, Department Biostatistics and Epidemiology)

  • Toine F. Cleophas

    (Technical University)

Abstract

Clinical trials often assess the efficacy of more than one new treatment and often use many efficacy variables. Also, after overall testing these efficacy variables, additional questions about subgroups differences or about what variables do or do not contribute to the efficacy results, remain. Assessment of such questions introduces the statistical problem of multiple comparison and multiple testing, which increases the risk of false positive statistical results, and thus increases the type-I error risk. In this chapter simple methods are discussed which can help to control this risk.

Suggested Citation

  • Ton J. Cleophas & Aeilko H. Zwinderman & Toine F. Cleophas, 2006. "Multiple Statistical Inferences," Springer Books, in: Statistics Applied to Clinical Trials, chapter 0, pages 87-96, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4020-4650-6_7
    DOI: 10.1007/978-1-4020-4650-6_7
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