A unique overview that melds the concepts of conditionalprobability and stochastic processes into real-lifeapplications
The role of randomization techniques in clinical trials has becomeincreasingly important. This comprehensive guide combines both theapplied aspects of randomization in clinical trials with aprobabilistic treatment of properties of randomization. Taking anunabashedly non-Bayesian and nonparametric approach to inference,the book focuses on the linear rank test under a randomizationmodel, with added discussion on likelihood-based inference as itrelates to sufficiency and ancillarity. Developments in stochasticprocesses and applied probability are also given where appropriate.Intuition is stressed over mathematics, but not without a cleardevelopment of the latter in the context of the former.

Providing a consolidated review of the field, the book includesrelevant and practical discussions of:
* The benefits of randomization in terms of reduction of bias
* Randomization as a basis for inference
* Covariate-adaptive and response-adaptive randomization
* Current philosophies, controversies, and new developments

With ample problem sets, theoretical exercises, and short computersimulations using SAS, Randomization in Clinical Trials: Theory andPractice is equally useful as a standard textbook in biostatisticsgraduate programs as well as a reliable reference forbiostatisticians in practice.