Modern Clinical Trial Analysis
Language: English
Published by Springer, 2012
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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£ 198.47
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - This volume covers classic as well as cutting-edge topics on the analysis of clinical trial data in biomedical and psychosocial research and discusses each topic in an expository and user-friendly fashion. The intent of the book is to provide an overview of the primary statistical and data analytic issues associated with each of the selected topics, followed by a discussion of approaches for tackling such issues and available software packages for carrying out analyses. While classic topics such as survival data analysis, analysis of diagnostic test data and assessment of measurement reliability are well known and covered in depth by available topic-specific texts, this volume serves a different purpose: it provides a quick introduction to each topic for self-learning, particularly for those who have not done any formal coursework on a given topic but must learn it due to its relevance to their multidisciplinary research. In addition, the chapters on these classic topics will reflect issues particularly relevant to modern clinical trials such as longitudinal designs and new methods for analyzing data from such study designs. The coverage of these topics provides a quick introduction to these important statistical issues and methods for addressing them. As with the classic topics, this part of the volume on modern topics will enable researchers to grasp the statistical methods for addressing these emerging issues underlying modern clinical trials and to apply them to their research studies.…
Seller Inventory # 9781461443216
- Title
- Modern Clinical Trial Analysis
- Author
- Xin Tu
- Publisher
- Springer
- Publication year
- 2012
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1461443210
- ISBN 13
- 9781461443216
- Item weight
- 565 grams
- Dimensions
- 241x160x19 mm
This volume covers classic as well as cutting-edge topics on the analysis of clinical trial data in biomedical and psychosocial research and discusses each topic in an expository and user-friendly fashion. The intent of the book is to provide an overview of the primary statistical and data analytic issues associated with each of the selected topics, followed by a discussion of approaches for tackling such issues and available software packages for carrying out analyses. While classic topics such as survival data analysis, analysis of diagnostic test data and assessment of measurement reliability are well known and covered in depth by available topic-specific texts, this volume serves a different purpose: it provides a quick introduction to each topic for self-learning, particularly for those who have not done any formal coursework on a given topic but must learn it due to its relevance to their multidisciplinary research. In addition, the chapters on these classic topics will reflect issues particularly relevant to modern clinical trials such as longitudinal designs and new methods for analyzing data from such study designs.
The coverage of these topics provides a quick introduction to these important statistical issues and methods for addressing them. As with the classic topics, this part of the volume on modern topics will enable researchers to grasp the statistical methods for addressing these emerging issues underlying modern clinical trials and to apply them to their research studies.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This volume covers classic as well as cutting-edge topics on the analysis of clinical trial data in biomedical and psychosocial research and discusses each topic in an expository and user-friendly fashion. Starting with survival data analysis, this book transitions from such a classic topic to modern issues by stepping through diagnostic test and instrument assessment, sequential and dynamic treatment regimen, cost-effectiveness evaluation, equivalence testing. As some type of cancer such as the effect of smoking on lung cancer cannot be studied using randomized trials, a chapter on analysis of non-randomized studies is also included. The book concludes with a chapter discussing the opportunities and challenges that lie ahead in developing on person-centered treatment regimens.
The book provides an overview of the primary statistical and data analytic issues associated with each of the selected topics, followed by a discussion of approaches for tackling such issues and available software packages for carrying out the analyses. Medical researchers with some background in clinical trial design and regression analysis as well as biostatisticians will find this book informative and helpful.
"About the title" may belong to another edition of this title.
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