Randomised Response-Adaptive Designs in Clinical Trials / Edition 1

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Randomised Response-Adaptive Designs in Clinical Trials presents methods for the randomised allocation of treatments to patients in sequential clinical trials. Emphasizing the practical application of clinical trial designs, the book is designed for medical and applied statisticians, clinicians, and statisticians in training.

After introducing clinical trials in drug development, the authors assess a simple adaptive design for binary responses without covariates. They discuss randomisation and covariate balance in normally distributed responses and cover many important response-adaptive designs for binary responses. The book then develops response-adaptive designs for continuous and longitudinal responses, optimum designs with covariates, and response-adaptive designs with covariates. It also covers response-adaptive designs that are derived by optimising an objective function subject to constraints on the variance of estimated parametric functions. The concluding chapter explores future directions in the development of adaptive designs.

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Editorial Reviews

From the Publisher
"This book is clearly written and well-structured for a graduate course as well as consulting statisticians. … this book is particularly useful for the development of orphan drugs."
Biometrics, March 2015

"… the book covers a very broad range of response-adaptive designs and related issues. … the book is comprehensively written and gives many exemplary applications from clinical practice. At the same time, the book is mathematically sound and also provides the underlying mathematical formulas and derivations. For these reasons, the book offers important content for applied statisticians but also for more theoretically interested mathematicians."
Biometrical Journal, 2014

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Product Details

Meet the Author

Anthony C. Atkinson is an Emeritus Professor of Statistics at the London School of Economics and Political Science.

Atanu Biswas is a professor in the Applied Statistics Unit at the Indian Statistical Institute, Kolkata.

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Table of Contents

Introduction: Stories and Data
Scope and Limits
Two-Treatment Trials with a Binary Response
Equal Randomisation
Adaptive Allocation
Urn Model
Some Motivating Clinical Trials

Adaptive Design: Controversies and Progress
Why Adaptive?
How Adaptive?
What Next?

Randomised Balanced Sequential Treatment Allocation
Balance with Two Treatments
Designs with Three or More Treatments
Designs with Covariates
The Distribution of Loss and of Bias
Heteroscedastic Models
More about Biased-Coin Designs
Further Reading

Response-Adaptive Designs for Binary Responses
Urn Designs
Play-the-Winner Rule
Randomised Play-the-Winner Rule
Generalised Pólya Urn
Success Driven Design (SDD)
Failure-Driven Design (FDD)
Birth and Death Urn (BDU)
Birth and Death Urn with Immigration
Drop-the-Loser Rule
Odds Ratio-Based Adaptive Designs
Delayed Response in the RPW Rule
Prognostic Factors in Urn Designs
Targeting an Allocation Proportion
Adaptive Designs for Categorical Responses
Comparisons and Recommendations

Response-Adaptive Designs for Continuous Responses
Some Trials with Continuous Responses
Doubly Adaptive Biased-Coin Designs (DBCD)
Nonparametric Designs
Adaptive Designs for Survival Data
Link Function-Based Adaptive Design (BB)
Multi-Treatment Multivariate Design
DL Rule for Continuous Responses (CDL)

Response-Adaptive Designs for Longitudinal Responses
Repeated Responses
Binary Longitudinal Responses (SLPW)
Design and Analysis for the PEMF Data
Longitudinal Categorical Responses
Longitudinal Multivariate Ordinal Responses
Models with Covariates
Continuous Longitudinal Responses
Random Number of Responses
Numerical Illustrations

Optimum Biased-Coin Designs with Covariates
Modelling and Design
Biased-Coin DA-Optimum Designs
Numerical Comparisons for Two Treatments
Designs for Three Treatments
Distribution of Loss
Skewed Allocations
Skewed Allocation – Numerical
Heteroscedastic Normal Models
Allocation Rules for Heteroscedastic Models
Generalized Linear Models
Binary Data
Allocation Rules for Binomial Models
Gamma Data
Loss, Power, Variability
Further Reading: Skewed Designs

Optimum Response-Adaptive Designs with Covariates
Link-Function-Based Adaptive Design
Adaptive Designs Maximising Utility
Power Comparisons for Four Rules
Redesigning a Trial: Fluoxetine Hydrochloride
Further Reading

Optimal Response-Adaptive Designs with Constraints
Optimal Designs Subject to Constraints
Design of Jennison and Turnbull
RSIHR Design
Maximising Power: Neyman Allocation
Other Designs
BM Design
ZR Design
A General Framework: BBZ Design
Two Normal Populations with Unknown Variances
Two-Sample Nonparametric Design
BM Design for More Than Two Treatments
Optimal Designs with More than One Constraint
Designs for Survival Times
Adaptive Constraints
Back to Chapter 7

Adaptive Design: Further Important Issues
Bayesian Adaptive Designs
Two-Stage Adaptive Design
Group Sequential Adaptive Design
Optimal Design for Binary Longitudinal Responses
Inverse Sampling
Robustness in Adaptive Designs
Missing Data in Response-Adaptive Designs
Asymptotic Results for CARA Designs
How to Bridge Theory and Practice

Appendix: Optimum Design



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