9780198565826-0198565828-The Statistical Evaluation of Medical Tests for Classification and Prediction (Oxford Statistical Science Series)

The Statistical Evaluation of Medical Tests for Classification and Prediction (Oxford Statistical Science Series)

ISBN-13: 9780198565826
ISBN-10: 0198565828
Edition: 1
Author: Margaret Sullivan Pepe
Publication date: 2004
Publisher: Oxford University Press
Format: Paperback 320 pages
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Book details

ISBN-13: 9780198565826
ISBN-10: 0198565828
Edition: 1
Author: Margaret Sullivan Pepe
Publication date: 2004
Publisher: Oxford University Press
Format: Paperback 320 pages

Summary

The Statistical Evaluation of Medical Tests for Classification and Prediction (Oxford Statistical Science Series) (ISBN-13: 9780198565826 and ISBN-10: 0198565828), written by authors Margaret Sullivan Pepe, was published by Oxford University Press in 2004. With an overall rating of 4.5 stars, it's a notable title among other Biology (Biological Sciences) books. You can easily purchase or rent The Statistical Evaluation of Medical Tests for Classification and Prediction (Oxford Statistical Science Series) (Paperback) from BooksRun, along with many other new and used Biology books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $16.6.

Description

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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