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Doody's Review ServiceReviewer: Sharon M. Homan, PhD (Kansas Health Institute)
Description: This book reviews basic principles of biostatistics and their use in biomedical and clinical research and decision making. The author organizes the text around hypothesis testing and estimation of treatment effects, and particularly emphasizes areas that the medical literature uses dubious practices (e.g., failure to adjust for multiple comparisons). This sixth edition is a substantial revision with updated examples and a complete redesign of illustrations, both improving the presentation of core statistical principles.
Purpose: It is oriented to students, postdoctoral research fellows, professors, and practitioners in medicine. The purpose is to review basic principles of biostatistics, with emphasis on mastering descriptive statistics, hypothesis testing, and research design. The book achieves these objectives using a straightforward teaching style of posing questions (e.g., How do you analyze rates and proportions?) and systematically demonstrating how to address the question. The content is interesting, practical, and is reinforced by review questions and summaries for each chapter.
Audience: This can be used as a text for medical students, health professionals, and researchers. Used as a required text for the biostatistics portion of the epidemiology and biostatistics course required of medical students, this book is clear, concise, and practical. The author is a professor of medicine at the Cancer Center of the University of California, San Francisco, who is recognized for his contributions to using biostatistics in clinical practice.
Features: The book teaches basic descriptive and inferential methods for one and two samples, introduces power, sample size, confidence intervals, and measurement. The author illustrates how to properly use statistical techniques including t tests, linear regression, analysis of variance, rank tests, Kaplan Meier survival curves, and Gehan tests. The highlights of the book are the chapter summaries, excellent examples, and final chapter, "What do the data really show?" The final chapter demonstrates how the research question, research design, and measurement influence the choice of statistical procedures. This edition greatly expands coverage of important statistical techniques used in the medical literature, but logistic regression is omitted. Logistic regression is used much more often in clinical and epidemiological research than linear regression.
Assessment: This well written book is highly useful for medical students and clinicians, and easy to understand. There are many introductory biostatistics and medical statistics texts, but three key features set this one apart: it assumes no prior knowledge of biostatistics, can be read and absorbed by the novice in about 15 hours, and greatly enhances the reader's ability to use and evaluate the clinical literature.