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Presents a firm mathematical basis for the use of response-adaptive randomization procedures in practice The Theory of Response-Adaptive Randomization in Clinical Trials is the result of the authors' ten-year collaboration as well as their collaborations with other researchers in investigating the important questions regarding response-adaptive randomization in a rigorous mathematical framework. Response-adaptive allocation has a long history in biostatistics literature; however, largely due to the disastrous ECMO trial in the early 1980s, there is a general reluctance to use these procedures. This timely book represents a mathematically rigorous subdiscipline of experimental design involvin...
This book encompasses a wide range of important topics. The articles cover the following areas: asymptotic theory and inference, biostatistics, economics and finance, statistical computing and Bayesian statistics, and statistical genetics. Specifically, the issues that are studied include large deviation, deviation inequalities, local sensitivity of model misspecification in likelihood inference, empirical likelihood confidence intervals, uniform convergence rates in density estimation, randomized designs in clinical trials, MCMC and EM algorithms, approximation of p-values in multipoint linkage analysis, use of mixture models in genetic studies, and design and analysis of quantitative traits.
This book is the first to offer a comprehensive examination of the pharmaceutical industry by following the tortuous course of a new drug as it progresses from early development to final delivery. Richard A. Epstein looks closely at the regulatory framework that surrounds all aspects of making pharmaceutical products today, and he assesses which current legal and regulatory practices make sense and which have gone awry. While critics of pharmaceutical companies call for ever more stringent controls on virtually every aspect of drug development and approval, Epstein cautions that the effect of such an approach will be to stifle pharmaceutical innovation and slow the delivery of beneficial tre...
A unique overview that melds the concepts of conditionalprobability and stochastic processes into real-lifeapplications The role of randomization techniques in clinical trials has becomeincreasingly important. This comprehensive guide combines both theapplied aspects of randomization in clinical trials with aprobabilistic treatment of properties of randomization. Taking anunabashedly non-Bayesian and nonparametric approach to inference,the book focuses on the linear rank test under a randomizationmodel, with added discussion on likelihood-based inference as itrelates to sufficiency and ancillarity. Developments in stochasticprocesses and applied probability are also given where appropriate.I...
This book constitutes the refereed proceedings of the Second International Conference on Web-Age Information Management, WAIM 2001, held in Xi'an, China, in July 2001. The 21 revised full papers and 12 short papers presented together with 4 research experience papers were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections on multimedia databases and high-dimensional indexing, information retrieval and text indexing, data mining, semistructured data management, data warehousing and federated databases, Web information management and e-commerce, spatio-temporal and high-dimensional information management, data mining and constraint management, data integration and filtering, and workflow and adaptive systems.
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This book constitutes the refereed proceedings of the 7th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2003, held in Seoul, Korea in April/Mai 2003. The 38 revised full papers and 20 revised short papers presented together with two invited industrial contributions were carefully reviewed and selected from 215 submissions. The papers are presented in topical sections on stream mining, graph mining, clustering, text mining, Bayesian networks, association rules, semi-structured data mining, classification, data analysis, and feature selection.
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