The Theory of Response-Adaptive Randomization in Clinical Trials represents a mathematically rigorous subdiscipline of experimental design involving randomization and answers fundamental questions.

Features:

• How does response-adaptive randomization affect power
• Can standard inferential tests be applied following response-adaptive randomization
• What is the effect of delayed response
• Which procedure is most appropriate and how can "most appropriate" be quantified
• How can heterogeneity of the patient population be incorporated
• Can response-adaptive randomization be performed with more than two treatments or with continuous responses

Contents

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

Likelihood-based Inference

• Data structure and Likelihood
• Asymptotic properties of maximum likelihood estimators

Procedures Based on Urn Models

• Generalized Friedman's urn
• The class of ternary urn models

Procedures Based on Sequential Estimation

• 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

Sample Size Calculation

• Power of a randomization procedure
• Three types of sample size

Additional Considerations

• The effect of delayed response
• Continuous responses
• Multiple (K > 2) treatments
• Accommodating heterogeneity

Implications for the Practice of Clinical Trials

• Standards
• Binary response
• Continuous responses
• The effect of delayed response

Incorporating Covariates

• General framework and asymptotic results
• Generalized linear models
• Two treatments with binary responses

Index

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