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"Multiple Comparisons" introduces simultaneous statistical inference and covers the theory and techniques for all-pairwise comparisons, multiple comparisons with the best, and multiple comparisons with a control. The author describes confidence intervals methods and stepwise exposes abuses and misconceptions, and guides readers to the correct method for each problem. Discussions also include the connections with bioequivalence, drug stability, and toxicity studies Real data sets analysed by computer software packages illustrate the applications presented.
"Multiple Comparisons" introduces simultaneous statistical inference and covers the theory and techniques for all-pairwise comparisons, multiple comparisons with the best, and multiple comparisons with a control. The author describes confidence intervals methods and stepwise exposes abuses and misconceptions, and guides readers to the correct method for each problem. Discussions also include the connections with bioequivalence, drug stability, and toxicity studies Real data sets analysed by computer software packages illustrate the applications presented.
Preface. Introduction to Simultaneous Statistical Inference. Classification of Multiple Comparison Methods. Multiple Comparisons With a Control. Multiple Comparisons With the Best. All-Pairwise Comparisons. Abuses and Misconceptions in Multiple Comparisons. Multiple Comparison in the General Linear Model. Some Useful Probabilistic Inequalities. Some Useful Geometric Lemmas. Sample Size Computations. Accessing Computer Codes. Tables of Critical Values. Bibliography. Subject Index.
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Jason Hsu
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