Feifang Hu & William F. Rosenberger 
The Theory of Response-Adaptive Randomization in Clinical Trials [PDF ebook] 

Dedication.
Preface.
1. Introduction.
1.1 Randomization in clinical trials.
1.2 Response-adaptive randomization in a historical context.
1.3 Outline of the book.
1.4 References.
2. Fundamental Questions of response-Adaptive
Randomization.
2.1 Optimal allocation.
2.2 The realtionship between power and response-adaptive
randomization.
2.3 The relationship for K > 2 treatments.
2.4 Asymptotically best procedures.
2.5 References.
3. Likelihood-based Inference.
3.1 Data structure and Likelihood.
3.2 Asymptotic properties of maximum likelihood estimators.
3.4 Conclusion.
3.5 References.
4. Procedures Based on Urn Models.
4.1 Generalized Friedman’s urn.
4.2 The class of ternary urn models.
4.3 References.
5. Procedures Based on Sequential Estimation.
5.1 Examples.
5.2 Properties of procedures based on sequential estimation for
K = 2.
5.3 Notation and conditions for the general framework.
5.4 Asymptotic results and some examples.
5.5 Proving the main theorems.
5.6 References.
6. Sample Size Calculation.
6.1 Power of a randomization procedure.
6.2 Three types of sample size.
6.3 Examples.
6.4 References.
7. Additional Considerations.
7.1 The effect of delayed response.
7.2 Continuous responses.
7.3 Multiple (K > 2) treatments.
7.4 Accommodating heterogeneity.
7.5 References.
8. Implications for the Practice of Clinical Trials.
8.1 Standards.
8.2 Binary response.
8.3 Continuous responses.
8.4 The effect of delayed response.
8.5 Conclusions.
8.6 References.
9. Incorporating Covariates.
9.1 Introduction and examples.
9.2 General framework and asymptotic results.
9.3 Generalized linear models.
9.4 Two treatments with binary responses.
9.5 Conclusions.
9.6 References.
10. Conclusions and Open Problems.
10.1 Conclusions.
10.2 Open problems.
10.3 References.
Appendix A: Supporting Technical Material.
A.1 Some matrix theory.
A.2 Jordan decomposition.
A.3 Matrix recursions.
A.4 Martingales.
A.5 Cramér-Wold device.
A.6 Multivariate martingales.
A.7 Multivariate Taylor’s expansion.
A.8 References.
Appendix B: Proofs.
B.1 Proofs theorems in Chapter 4.
B.2 Proof of theorems in Chapter 5.
B.3 Proof of theorems in Chapter 7.
B.4 References.
Author Index.
Subject Index.

FEIFANG HU, Ph D, 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, Ph D, 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,
he has authored over fifty refereed articles and edited two
monographs.