John Aitchison, Jim W. Kay, Ian J. Lauder

"… 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

• Preface. The Field of Application. Relating the Present Patient to Past Experience. A Review of Statistical Methodology. Further Statistical Methodology. Experience. Observation and Measurement. Indirect Measurement: Assay and Calibration. Diagnosis. Special Aspects of Diagnosis. Prognosis. Assessment. Data Sets and Software. References. Author Index. Subject Index.

John Aitchison, Jim W. Kay, Ian J. Lauder

"… 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

• Preface. The Field of Application. Relating the Present Patient to Past Experience. A Review of Statistical Methodology. Further Statistical Methodology. Experience. Observation and Measurement. Indirect Measurement: Assay and Calibration. Diagnosis. Special Aspects of Diagnosis. Prognosis. Assessment. Data Sets and Software. References. Author Index. Subject Index.