Abstract
In this chapter, we shall study multiple decision procedures in terms of hypotheses-testing problems. First, we discuss the conditional confidence approach of Kiefer which can be used to improve Neyman-Pearson (NP) formulation. This is done in Section 6.2. Using this approach, we describe conditional selection procedures and their relation with classical selection rules. Later, we discuss the theory of multiple comparisons for some appropriate alternative hypotheses. In Section 6.3, we consider an optimal criterion to improve the power of the individual test. Using this approach, we derive selection rules based on tests. Multiple range tests are studied in Section 6.4. A discussion of the multistage comparison procedures is provided in Section 6.5.
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Gupta, S.S., Huang, DY. (1981). Multiple Decision Procedures Based on Tests. In: Multiple Statistical Decision Theory: Recent Developments. Lecture Notes in Statistics, vol 6. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-5925-1_6
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DOI: https://doi.org/10.1007/978-1-4612-5925-1_6
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