- Series: Guilford School Practitioner
- Hardcover: 296 pages
- Publisher: Chapman and Hall/CRC; 1 edition (February 1, 1996)
- Language: English
- ISBN-10: 0412982811
- ISBN-13: 978-0412982811
- Product Dimensions: 6.1 x 0.7 x 9.2 inches
- Shipping Weight: 1.2 pounds (View shipping rates and policies)
- Average Customer Review: 1 customer review
- Amazon Best Sellers Rank: #356,895 in Books (See Top 100 in Books)
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Multiple Comparisons: Theory and Methods (Guilford School Practitioner) 1st Edition
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From the Back Cover
Multiple comparisons are the comparisons of two or more treatments. These may be treatments of a disease, groups of subjects, or computer systems, for example. Statistical multiple comparison methods are used heavily in research, education, business, and manufacture to analyze data, but are often used incorrectly. This book exposes such abuses and misconceptions, and guides the reader to the correct method of analysis for each problem. Theories for all-pairwise comparisons, multiple comparison with the best, and multiple comparison with a control are discussed, and methods giving statistical inference in terms of confidence intervals, confident directions, and confident inequalities are described. Applications are illustrated with real data. Included are recent methods empowered by modern computers. Multiple Comparisons will be valued by researchers and graduate students interested in the theory of multiple comparisons, as well as those involved in data analysis in biological and social sciences, medicine, business and engineering. It will also interest professional and consulting statisticians in the pharmaceutical industry, and quality control engineers in manufacturing companies.
Top customer reviews
Since that time the methods and applications continue to grow. Hsu provides a systematic treatment and makes the material accessible. The literature is often disjoint and confusing but Hsu puts things together very well and provides a wealth of applications in a variety of disciplines including pharmaceuticals and quality control engineering.
The book is also very valuable because it exposes the misuses. It is probably the best current reference source for this subject. I have used it as a refrerence in statistical analysis plans and sections of protocols that I have written for clinical trials at various pharmaceutical companies. One of the things that I like best about the text are the simple proofs of important practical theorems. My favorite example is the proof that closed testing maintains the type I error rate without the need for a multiplicity adjustment.