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Statistical Concepts and Applications in Clinical Medicine presents a unique, problem-oriented approach to using statistical methods in clinical medical practice through each stage of the clinical process, including observation, diagnosis, and treatment. The authors present each consultative problem in its original form, then describe the process of problem formulation, develop the appropriate statistical models, and interpret the statistical analysis in the context of the real problem. Their treatment provides clear, accessible explanations of statistical methods. The text includes end-of-chapter exercises that help develop formulatory, analytic, and interpretative skills.
Review Quotes
1. "the style of the authors makes for dynamic reading: the reader feels a part of the scientific endeavor which is almost like solving a mystery. This book will be fun to read and useful in practice." -William F. Rosenberger, University of Maryland, USA "The book presents a fascinating insight into the consultant statistician/clinician interaction. It is beautifully written and the style of motivating theory by extended real examples is very effective. It is not in the usual mould of the book on medical statistics: the order of the exposition brings medicine to the fore for example. The clinical examples are clearly described. The Bayesian approach is gently introduced, there is nothing doctrinaire about it, the experience of the individual patient is considered through predictive probabilities." this text looks like a classic in the making I am not aware of a comparable book. It should be accessible to the more statistically aware physician whilst being of interest to the medical statistician especially those involved in consulting, I would certainly recommend it to many of my clinical consultees. It should be a standard text held by medical school libraries and medical institutes." -Peter W. Jones, Keele University, UK "[I]t covers topics that are not usually addressed in medical statistics or clinical trials textbooksAs a statistician engaged in pharmaceutical drug development, I found the discussion about interactions with medical professionals in Chapter 1 to be very useful. I also found the discussions concerning compositional data including the pitfalls in using conventional correlational analyses with compositional data in Chapter 4 to be helpfulIf the ideal of individualizedtherapy becomes a reality in the future, this book may become a standard reference." -Journal of Biopharmaceutical Statistics
2.
" the style of the authors makes for dynamic reading: the reader feels a part of the scientific endeavor which is almost like solving a mystery. This book will be fun to read and useful in practice "
William F. Rosenberger, University of Maryland
"The book presents fascinating insight into the consultant statistician/clinician interaction. It is beautifully written and the style of motivating theory by extended real examples is very effective. It is not in the usual mould of the book on medical statistics: the order of the exposition brings medicine to the fore for example. The clinical examples are clearly described. The Bayesian approach is gently introduced; there is nothing doctrinaire about it, the experience of the individual patient is considered through predictive probabilities. this text looks like a classic in the making; I am not aware of a comparable book. It should be accessible to the more statistically aware physician whilst being of interest to the medical statistician, especially those involved in consulting. I would certainly recommend it to many of my clinical consultees. It should be a standard text held by medical school libraries and medical institutes."
Peter W. Jones, Keele University"
3.
" the style of the authors makes for dynamic reading: the reader feels a part of the scientific endeavor which is almost like solving a mystery. This book will be fun to read and useful in practice "
William F. Rosenberger, University of Maryland
"The book presents fascinating insight into the consultant statistician/clinician interaction. It is beautifully written and the style of motivating theory by extended real examples is very effective. It is not in the usual mould of the book on medical statistics: the order of the exposition brings medicine to the fore for example. The clinical examples are clearly described. The Bayesian approach is gently introduced; there is nothing doctrinaire about it, the experience of the individual patient is considered through predictive probabilities. this text looks like a classic in the making; I am not aware of a comparable book. It should be accessible to the more statistically aware physician whilst being of interest to the medical statistician, especially those involved in consulting. I would certainly recommend it to many of my clinical consultees. It should be a standard text held by medical school libraries and medical institutes."
Peter W. Jones, Keele University
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