Authors: William F. Rosenberger, John M. Lachin
A unique overview that melds the concepts of conditional probability and stochastic processes into real-life applications The role of randomization techniques in clinical trials has become increasingly important. This comprehensive guide combines both the
applied aspects of randomization in clinical trials with a probabilistic treatment of properties of randomization. Taking an unabashedly non-Bayesian and
nonparametric approach to inference, the book 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 also given where…
