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Theory of Response-Adaptive Randomization in Clinical Trials

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ISBN-10: 0470055871

ISBN-13: 9780470055878

Edition: 2006

Authors: Feifang Hu, William F. Rosenberger

List price: $139.00
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Book details

List price: $139.00
Copyright year: 2006
Publisher: John Wiley & Sons, Incorporated
Publication date: 9/29/2006
Pages: 232
Language: English

FEIFANG HU, PhD, is Associate Professor in the Department of Statistics at the University of Virginia. He is the recipient of numerous grants, honors, and awards. His research interests include biostatistics, applied probability and statistical inference, and resampling methods. He has authored over forty refereed articles.WILLIAM F. ROSENBERGER, PhD, is Professor and Chair of the Department of Applied and Engineering Statistics at George Mason University. He received the Association of American Publishers' Professional/Scholarly Publishing Award in 2002 for his coauthored work, Randomization in Clinical Trials: Theory And Practice (Wiley). A Fellow of the American Statistical Association,…    

FEIFANG HU, PhD, is Associate Professor in the Department of Statistics at the University of Virginia. He is the recipient of numerous grants, honors, and awards. His research interests include biostatistics, applied probability and statistical inference, and resampling methods. He has authored over forty refereed articles.WILLIAM F. ROSENBERGER, PhD, is Professor and Chair of the Department of Applied and Engineering Statistics at George Mason University. He received the Association of American Publishers' Professional/Scholarly Publishing Award in 2002 for his coauthored work, Randomization in Clinical Trials: Theory And Practice (Wiley). A Fellow of the American Statistical Association,…    

Dedication
Preface
Introduction
Randomization in clinical trials
Response-adaptive randomization in a historical context
Outline of the book
References
Fundamental Questions of response-Adaptive Randomization
Optimal allocation
The realtionship between power and response-adaptive randomization
The relationship for K > 2 treatments
Asymptotically best procedures
References
Likelihood-based Inference
Data structure and Likelihood
Asymptotic properties of maximum likelihood estimators
Conclusion
References
Procedures Based on Urn Models
Generalized Friedman's urn
The class of ternary urn models
References
Procedures Based on Sequential Estimation
Examples
Properties of procedures based on sequential estimation for K = 2
Notation and conditions for the general framework
Asymptotic results and some examples
Proving the main theorems
References
Sample Size Calculation
Power of a randomization procedure
Three types of sample size
Examples
References
Additional Considerations
The effect of delayed response
Continuous responses
Multiple (K > 2) treatments
Accommodating heterogeneity
References
Implications for the Practice of Clinical Trials
Standards
Binary response
Continuous responses
The effect of delayed response
Conclusions
References
Incorporating Covariates
Introduction and examples
General framework and asymptotic results
Generalized linear models
Two treatments with binary responses
Conclusions
References
Conclusions and Open Problems
Conclusions
Open problems
References
Supporting Technical Material
Some matrix theory
Jordan decomposition
Matrix recursions
Martingales
Cram�r-Wold device
Multivariate martingales
Multivariate Taylor's expansion
References
Proofs
Proofs theorems in Chapter 4
Proof of theorems in Chapter 5
Proof of theorems in Chapter 7
References
Author Index
Subject Index