Elementary Bayesian Biostatistics

With numerous exercises and a CD-ROM of data sets and computing code, this lucid introduction explores Bayesian principles and illustrates their application to healthcare research. It reviews the interesting and controversial history of the Bayesian concept and enables a balanced comparison of Bayesian tools with standard frequentist approaches. The book also discusses several important implementations of Bayesian procedures in clinical research, including sample size computations, adaptive randomization, and monitoring procedures. In addition, it shows how to evaluate a healthcare research scenario to determine whether a frequentist or Bayesian approach is most appropriate.

Bayesian analyses have made important inroads in modern clinical research due, in part, to the incorporation of the traditional tools of noninformative priors as well as the modern innovations of adaptive randomization and predictive power. Presenting an introductory perspective to modern Bayesian procedures, Elementary Bayesian Biostatistics explores Bayesian principles and illustrates their application to healthcare research.

Building on the basics of classic biostatistics and algebra, this easy-to-read book provides a clear overview of the subject. It focuses on the history and mathematical foundation of Bayesian procedures, before discussing their implementation in healthcare research from first principles. The author also elaborates on the current controversies between Bayesian and frequentist biostatisticians. The book concludes with recommendations for Bayesians to improve their standing in the clinical trials community. Calculus derivations are relegated to the appendices so as not to overly complicate the main text.

As Bayesian methods gain more acceptance in healthcare, it is necessary for clinical scientists to understand Bayesian principles. Applying Bayesian analyses to modern healthcare research issues, this lucid introduction helps readers make the correct choices in the development of clinical research programs.