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Optimized Response-Adaptive Clinical Trials : Sequential Treatment Allocation Based on Markov Decision Problems / by Thomas Ondra
(BestMasters. ISSN:26253615)
版 | 1st ed. 2015. |
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出版者 | Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Spektrum |
出版年 | 2015 |
本文言語 | 英語 |
大きさ | XV, 102 p. 14 illus : online resource |
著者標目 | *Ondra, Thomas author SpringerLink (Online service) |
件 名 | LCSH:Mathematics -- Data processing
全ての件名で検索
LCSH:Probabilities LCSH:Mathematical analysis FREE:Computational Mathematics and Numerical Analysis FREE:Probability Theory FREE:Analysis |
一般注記 | Introduction to Markov Decision Problems and Examples -- Finite and Infinite Horizon Markov Decision Problems -- Solution Algorithms: Backward Induction, Value Iteration and Policy Iteration -- Designing Response Adaptive Clinical Trials with Markov Decision Problems Two-armed response-adaptive clinical trials are modelled as Markov decision problems to pursue two overriding objectives: Firstly, to identify the superior treatment at the end of the trial and, secondly, to keep the number of patients receiving the inferior treatment small. Such clinical trial designs are very important, especially for rare diseases. Thomas Ondra presents the main solution techniques for Markov decision problems and provides a detailed description how to obtain optimal allocation sequences. Contents Introduction to Markov Decision Problems and Examples Finite and Infinite Horizon Markov Decision Problems Solution Algorithms: Backward Induction, Value Iteration and Policy Iteration Designing Response Adaptive Clinical Trials with Markov Decision Problems Target Groups Researchers and students in the fields of mathematics and statistics Professionals in the pharmaceutical industry< The Author Thomas Ondra obtained his Master of Science degree in mathematics at University of Vienna. He is a research assistant and PhD student at the Section for Medical Statistics of Medical University of Vienna. HTTP:URL=https://doi.org/10.1007/978-3-658-08344-1 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9783658083441 |
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EB00234590 |
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