A Bayesian Approach to Successive Comparisons

10.6339/JDS.2010.08(4).630

A. Aghamohammadi；M. R. Meshkani；M. Mohammadzadeh

Bayesian inference ； familywise error rate ； MCMC ； multiple comparisons

Journal of Data Science

8卷4期（2010 / 10 / 01）

541 - 553

英文

The present article discusses and compares multiple testing procedures (MTPs) for controlling the family wise error rate. Machekano and Hubbard (2006) have proposed empirical Bayes approach that is a resampling based multiple testing procedure asymptotically controlling the familywise error rate. In this paper we provide some additional work on their procedure, and we develop resampling based step-down procedure asymptotically controlling the familywise error rate for testing the families of one-sided hypotheses. We apply these procedures for making successive comparisons between the treatment effects under a simple-order assumption. For example, the treatment means may be a sequences of increasing dose levels of a drug. Using simulations, we demonstrate that the proposed step-down procedure is less conservative than the Machekano and Hubbard's procedure. The application of the procedure is illustrated with an example.

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