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Handbook of multiple comparisons /

Cui, Xinping,

Handbook of multiple comparisons /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Handbook of multiple comparisons /Xinping Cui ... [et al.] (eds.).
其他作者:	Cui, Xinping,
出版者:	Boca Raton :CRC Press,2022.
面頁冊數:	xiv, 404 p. :ill. ;26 cm.
標題:	Multiple comparisons (Statistics)
ISBN:	9780367140670 :

Handbook of multiple comparisons /
Handbook of multiple comparisons /Xinping Cui ... [et al.] (eds.). - 1st ed. - Boca Raton :CRC Press,2022. - xiv, 404 p. :ill. ;26 cm. - Chapman & Hall/CRC handbooks of modern statistical methods.

Includes bibliographical references and index.

"Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparisonproblems big and small, with guidance toward error rate control and insightson how principles developed earlier can be applied to current and emergingproblems. Some highlights of the coverages are as follows. Error ratecontrol is useful for controlling the incorrect decision rate. Chapter 1introduces Tukey's original multiple comparison error rates and point to howthey have been applied and adapted to modern multiple comparison problems asdiscussed in the later chapters. Principles endure. While the closed testingprinciple is more familiar, Chapter 4 shows the partitioning principle canderive confidence sets for multiple tests, which may become important as theprofession goes beyond making decisions based on p-values. Multiple comparisons of treatment efficacy often involve multiple doses and endpoints. Chapter 12 on multiple endpoints explains how different choicesof endpoint types lead to different multiplicity adjustment strategies,while Chapter 11 on the MCP-Mod approach is particularly useful for dose-finding. To assess efficacy in clinical trials with multiple doses andmultiple endpoints, the reader can see the traditional approach in Chapter2, the Graphical approach in Chapter 5, and the multivariate approach inChapter 3. Personalized/precision medicine based on targeted therapies,already a reality, naturally leads to analysis of efficacy in subgroups.Chapter 13 draws attention to subtle logical issues in inferences onsubgroups and their mixtures, with a principled solution that resolves these issues. This chapter has implication toward meeting the ICHE9R1 Estimands requirement. Besides the mere multiple testing methodology itself, thehandbook also covers related topics like the statistical task of modelselection in Chapter 7 or the estimation of the proportion of true nullhypotheses (or, in other words, the signal prevalence) in Chapter 8. It alsocontains decision-theoretic considerations regarding the admissibility ofmultiple tests in Chapter 6. The issue of selected inference is addressed inChapter 9. Comparison of responses can involve millions of voxels in medicalimaging or SNPs in genome-wide association studies (GWAS). Chapter 14 andChapter 15 provide state of the art methods for large scale simultaneous inference in these settings"--

ISBN: 9780367140670 :NT$6166

LCCN: 2021020343Subjects--Topical Terms:

377560
Multiple comparisons (Statistics)

LC Class. No.: QA278.4 / .H36 2021

Dewey Class. No.: 519.5/35

Handbook of multiple comparisons /
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300 $a xiv, 404 p. : $b ill. ; $c 26 cm.
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504 $a Includes bibliographical references and index.
520 $a "Written by experts that include originators of some key ideas, chapters in the Handbook of Multiple Testing cover multiple comparisonproblems big and small, with guidance toward error rate control and insightson how principles developed earlier can be applied to current and emergingproblems. Some highlights of the coverages are as follows. Error ratecontrol is useful for controlling the incorrect decision rate. Chapter 1introduces Tukey's original multiple comparison error rates and point to howthey have been applied and adapted to modern multiple comparison problems asdiscussed in the later chapters. Principles endure. While the closed testingprinciple is more familiar, Chapter 4 shows the partitioning principle canderive confidence sets for multiple tests, which may become important as theprofession goes beyond making decisions based on p-values. Multiple comparisons of treatment efficacy often involve multiple doses and endpoints. Chapter 12 on multiple endpoints explains how different choicesof endpoint types lead to different multiplicity adjustment strategies,while Chapter 11 on the MCP-Mod approach is particularly useful for dose-finding. To assess efficacy in clinical trials with multiple doses andmultiple endpoints, the reader can see the traditional approach in Chapter2, the Graphical approach in Chapter 5, and the multivariate approach inChapter 3. Personalized/precision medicine based on targeted therapies,already a reality, naturally leads to analysis of efficacy in subgroups.Chapter 13 draws attention to subtle logical issues in inferences onsubgroups and their mixtures, with a principled solution that resolves these issues. This chapter has implication toward meeting the ICHE9R1 Estimands requirement. Besides the mere multiple testing methodology itself, thehandbook also covers related topics like the statistical task of modelselection in Chapter 7 or the estimation of the proportion of true nullhypotheses (or, in other words, the signal prevalence) in Chapter 8. It alsocontains decision-theoretic considerations regarding the admissibility ofmultiple tests in Chapter 6. The issue of selected inference is addressed inChapter 9. Comparison of responses can involve millions of voxels in medicalimaging or SNPs in genome-wide association studies (GWAS). Chapter 14 andChapter 15 provide state of the art methods for large scale simultaneous inference in these settings"-- $c Provided by publisher.
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