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The approach taken in this book is, to studies monitored over time, what the Central Limit Theorem is to studies with only one analysis. Just as the Central Limit Theorem shows that test statistics involving very different types of clinical trial outcomes are asymptotically normal, this book shows that the joint distribution of the test statistics at different analysis times is asymptotically multivariate normal with the correlation structure of Brownian motion ("the B-value") - irrespective of the test statistic. Thus, this book offers statisticians an accessible, incremental approach to understanding Brownian motion as related to clinical trials.

Statistical Monitoring of Clinical Trials: A Unified Approach

A General Framework.- Power: Conditional, Unconditional, and Predictive.- Historical Monitoring Boundaries.- Spending Functions.- Practical Survival Monitoring.- Inference Following a Group-Sequential Trial.- Options When Brownian Motion Does Not Hold.- Monitoring for Safety.- Bayesian Monitoring.- Adaptive Sample Size Methods.- Topics Not Covered.- Appendix I: The Logrank and Related Tests.- Appendix II: Group-Sequential Software.