This book describes statistical concepts and techniques for evaluating medical diagnostic tests and biomarkers for detecting disease. More generally, the techniques pertain to the statistical classification problem for predicting a dichotomous outcome. Measures for quantifying test accuracy are described including sensitivity, specificity, predictive values, diagnostic likelihood ratios and the Receiver Operating Characteristic Curve that is commonly used for continuous and ordinal valued tests. Statistical procedures are presented for estimating and comparing them. Regression frameworks for assessing factors that influence test accuracy and for comparing tests while adjusting for such factors are presented. This book presents many worked examples of real data and should be of interest to practicing statisticians or quantitative researchers involved in the development of tests for classification or prediction in medicine.
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Statistical results are given a methodical treatment. In each chapter statistical results are motivated, stated and usually proven, and then illustrated on a variety of datasets based on actual trials. Many of the results were developed by Pepe and her colleagues, who have advanced the field in seminal ways. Chapters end with a concluding remarks section, a set of exercises, and proofs of more involved theoretical results, when needed. Concluding remarks sections nicely summarize results and discuss open research questions. References to key papers are given throughout. This structure allows the book to serve as both a classroom text and an excellent reference to the current literature. (Journal of Biopharmaceutical Studies)
I very much recommend this book to a range of audiences, from those wanting an introduction to diagnostic test concepts and methods to active researchers in the area. This book is likely to stimulate considerable progress in development of new statistical methods for diagnostic tests, an area that relative to therapeutics has received little attention from biostatisticians. (Journal of Biopharmaceutical Studies)
Margaret Sullivan Pepe is a Professor of Biostatistics, University of Washington; Fred Hutchinson Cancer Research Center, Washington, U.S.A. . Margaret Sullivan Pepe is a Professor of Biostatistics, University of Washington; Fred Hutchinson Cancer Research Center, Washington, U.S.A. .
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Paperback. Condition: Good. This book describes statistical concepts and techniques for evaluating medical diagnostic tests and biomarkers for detecting disease. More generally, the techniques pertain to the statistical classification problem for predicting a dichotomous outcome. Measures for quantifying test accuracy are described including sensitivity, specificity, predictive values, diagnostic likelihood ratios and the Receiver Operating Characteristic Curve that is commonly used for continuous and ordinal valued tests. Statistical procedures are presented for estimating and comparing them. Regression frameworks for assessing factors that influence test accuracy and for comparing tests while adjusting for such factors are presented. This book presents many worked examples of real data and should be of interest to practicing statisticians or quantitative researchers involved in the development of tests for classification or prediction in medicine. Seller Inventory # 00107482393
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Paperback. Condition: Good. This book describes statistical concepts and techniques for evaluating medical diagnostic tests and biomarkers for detecting disease. More generally, the techniques pertain to the statistical classification problem for predicting a dichotomous outcome. Measures for quantifying test accuracy are described including sensitivity, specificity, predictive values, diagnostic likelihood ratios and the Receiver Operating Characteristic Curve that is commonly used for continuous and ordinal valued tests. Statistical procedures are presented for estimating and comparing them. Regression frameworks for assessing factors that influence test accuracy and for comparing tests while adjusting for such factors are presented. This book presents many worked examples of real data and should be of interest to practicing statisticians or quantitative researchers involved in the development of tests for classification or prediction in medicine. Seller Inventory # CIN0198565828G
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