by William F. Rosenberger, John M. Lachin

This Second Edition features a unique overview that melds the concepts of conditional probability and stochastic processes into real-life applications.  By combining the applied aspects of randomization in clinical trials with a nonparametric approach to inference, the book has become a 'must have' for biostatisticians and pharmaceutical industry statisticians.  The book also focuses on the linear rank test under a randomization model, with added discussion on likelihood-based inference as it relates to sufficiency and ancillarity.Developments in stochastic processes and applied probability are presented where appropriate and includes response-adaptive randomization, Bayesian designs, CARA randomization, and covariate-adaptive randomization in theory and practice.  Additional coverage of "randomization in practice", such as cluster randomization, new developments in restricted randomization, and increased discussions on philosophical issues in randomization, have also been included.  This new edition also has an increased focus on computation of randomized tests rather than the asymptotic theory of randomized tests.  Chapter coverage includes: randomization and the clinical trial; issues in the design of clinical trials; restrited randomization; balancing on covariates; accidental bias; selection bias; randomization as a basis for inference; inference for stratified, blocked, and covariate-adjusted analysesl randomization in practice; cluster randomization; response-adaptive randomization; response-adaptive randomization in practice; inference for response-adaptive and covariate-adaptive randomization; and covariate-adjusted response-adaptive randomization.

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