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 analyzed by computer software packages illustrate the applications presented.
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34 of 34 people found the following review helpful:
5.0 out of 5 stars
very good modern treatment of multiple comparison issues,
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This review is from: Multiple Comparisons: Theory and Methods (Hardcover)
Rupert Miller's book "Simultaneous Statistical Inference" was acclaimed when it was published in 1966 as a source that unified the scattered literature on the topic. In 1981, the second edition provided a welcomed update.
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.
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This chapter discusses simultaneous statistical inference, that is, inference on several parameters at once, in a setting simpler than multiple comparisons inference, which is simultaneous inference on certain functions of the differences of the treatment effects. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
confident directions method, closed testing method, directional assertions, significant difference inference, pairwise ranking methods, stepup method, stepdown method, following simultaneous confidence intervals, underlining scheme, smaller treatment effect, larger treatment effect, new treatment worse, asymptotic multivariate normality, sample size computation, multiple comparison methods, probabilistic inequalities, directional inference, incorrect assertion, random indices, practical equivalence, standard suture, ith treatment, many new treatments, correct simultaneously, inequalities method Key Phrases - Capitalized Phrases (CAPs): (learn more)
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
This chapter discusses simultaneous statistical inference, that is, inference on several parameters at once, in a setting simpler than multiple comparisons inference, which is simultaneous inference on certain functions of the differences of the treatment effects. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
confident directions method, closed testing method, directional assertions, significant difference inference, pairwise ranking methods, stepup method, stepdown method, following simultaneous confidence intervals, underlining scheme, smaller treatment effect, larger treatment effect, new treatment worse, asymptotic multivariate normality, sample size computation, multiple comparison methods, probabilistic inequalities, directional inference, incorrect assertion, random indices, practical equivalence, standard suture, ith treatment, many new treatments, correct simultaneously, inequalities method Key Phrases - Capitalized Phrases (CAPs): (learn more)
Oude Voshaar, Yummy Cat Chow, Level Lower Center Upper, Treatment Observation New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 26
books:
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52
books
cite this book:
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- Residuals and Influence in Regression (Monographs on Statistics and Applied Probability, 18) by R. Dennis Cook in Back Matter
- Cyclic Designs (Monographs on Statistics and Applied Probability) by J. A. John in Back Matter
- Nonparametrics: Statistical Methods Based on Ranks by Erich L. Lehmann in Back Matter
- Matrices With Applications by Hugh G. Campbell in Back Matter
- Mathematical Statistics by B. L. Van Der Waerden in Back Matter
See all 26 books this book cites
- Multiple Comparisons and Multiple Tests Using the SAS System by Peter Westfall on 11 pages
- Design and Analysis of Experiments (Springer Texts in Statistics) by Angela M. Dean on 7 pages
- Simulation Modeling and Analysis (Industrial Engineering and Management Science Series) by Averill Law on 4 pages
- Dose Finding in Drug Development (Statistics for Biology and Health) by Naitee Ting on page 171, page 198, and page 217
- Statistics for Environmental Biology and Toxicology (Chapman & Hall/CRC Interdisciplinary Statistics) by A. John Bailer on page 184, and Back Matter
See all 52 books citing this book
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