Bayesian Thinking in Biostatistics.

Abstract

Bayesian statistics is becoming more and more popular in biostatistics partly because (a) there is almost always prior information available, (b) uncertainty quantification is crucial in biological and biomedical applications, (c) adaptiveness is desired for modern clinical trial design, and (d) the increasing complexity of data and scientific questions calls for more flexible statistical models. Despite its fast growing popularity, Bayesian statistics has not been widely taught at the introductory level yet and hence scientists from other disciplines often do not have the right tools in their toolboxes to apply Bayesian methods to their research. This textbook aims to introduce Bayesian statistics to intro-level biostatistics courses, which could benefit students majored in biostatistics as well as nonstatisticians who are interested in Bayesian biostatistics. Overall, I enjoy reading the book very much.