Multiple testing problem in pharmaceutical statistics
By: Dmitrienko, Alex.
Contributor(s): Tamhane, Ajit C.Bretz, Frank.
Publisher: NA CRC Press 2010Edition: 1st.Description: 304, 24*16.1 Pages | Binding - Paperback |.ISBN: 1-58488-984-7.Subject(s): PHARMACEUTICSDDC classification: 615.1401513 Online resources: Click here to access online Summary: Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple comparison research with an emphasis on pharmaceutical applications. In each chapter, the expert contributors describe important multiplicity problems encountered in pre-clinical and clinical trial settings. The book begins with a broad introduction from a regulatory perspective to different types of multiplicity problems that commonly arise in confirmatory controlled clinical trials, before giving an overview of the concepts, principles, and procedures of multiple testing. It then presents statistical methods for analyzing clinical dose response studies that compare several dose levels with a control as well as statistical methods for analyzing multiple endpoints in clinical trials. After covering gatekeeping procedures for testing hierarchically ordered hypotheses, the book discusses statistical approaches for the design and analysis of adaptive designs and related confirmatory hypothesis testing problems. The final chapter focuses on the design of pharmacogenomic studies based on established statistical principles. It also describes the analysis of data collected in these studies, taking into account the numerous multiplicity issues that occur. This volume explains how to solve critical issues in multiple testing encountered in pre-clinical and clinical trial applications. It presents the necessary statistical methodology, along with examples and software code to show how to use the methods in practice.Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|
Text Books | School of Pharmacy Reference Section | Reference | 615.1401513 DMI/TAM (Browse shelf) | Not For Loan | B0817 |
Browsing School of Pharmacy Shelves , Shelving location: Reference Section , Collection code: Reference Close shelf browser
No cover image available | No cover image available | No cover image available | ||||||
615.14 SAN/MEH Dispensing pharmacy | 615.1401513 BAL/GRE Pharmacy calculation | 615.1401513 DE Basic statistics and pharmaceutical stastical application | 615.1401513 DMI/TAM Multiple testing problem in pharmaceutical statistics | 615.1401513 GRA Statistical quality control | 615.1401513 JAI Pharmaceutical arithmetic | 615.1401513 MOI Pharmaceutical calculations |
Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple comparison research with an emphasis on pharmaceutical applications. In each chapter, the expert contributors describe important multiplicity problems encountered in pre-clinical and clinical trial settings.
The book begins with a broad introduction from a regulatory perspective to different types of multiplicity problems that commonly arise in confirmatory controlled clinical trials, before giving an overview of the concepts, principles, and procedures of multiple testing. It then presents statistical methods for analyzing clinical dose response studies that compare several dose levels with a control as well as statistical methods for analyzing multiple endpoints in clinical trials. After covering gatekeeping procedures for testing hierarchically ordered hypotheses, the book discusses statistical approaches for the design and analysis of adaptive designs and related confirmatory hypothesis testing problems. The final chapter focuses on the design of pharmacogenomic studies based on established statistical principles. It also describes the analysis of data collected in these studies, taking into account the numerous multiplicity issues that occur.
This volume explains how to solve critical issues in multiple testing encountered in pre-clinical and clinical trial applications. It presents the necessary statistical methodology, along with examples and software code to show how to use the methods in practice.
There are no comments for this item.