Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis

must be constrained (Example 7.26), use of the step function in computing the probability that a team would rank best or worst in a league (Example 5.10), and implementation of a Dirichlet process prior (Example 6.27). The comprehensive 19-page reference list consists primarily of statistics books and journals (both applied and methodological), and also includes journals in applications areas from which worked examples are drawn (e.g., Cognitive Science, British Journal of Cancer, Virology, Health Economics, and ScientiŽ c American). Unfortunately, due possibly to poor proofreading, the book contains so many confusing misstatements that its usefulness as an introductory text is very limited. The following are two representative examples. In Chapter 2, in which Congdon presents the basic Bayesian framework in the context of preparing for a Bayesian test of hypotheses, he states (p. 15):