Statistical Methods in Diagnostic Medicine (Wiley Series in Probability and Statistics) |  | Authors: Xiao-Hua Zhou, Donna K. McClish, Nancy A. Obuchowski
Publisher: Wiley-Interscience
List Price: $145.00
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Rating:  2 reviews
Sales Rank: 194800
Media: Hardcover
Edition: 1
Pages: 464
Number Of Items: 1
Shipping Weight (lbs): 1.7
Dimensions (in): 9.4 x 6.3 x 1
ISBN: 0471347728
Dewey Decimal Number: 616
EAN: 9780471347729
ASIN: 0471347728
Publication Date: July 22, 2002
Availability: Usually ships in 1-2 business days
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Product Description
An important role of diagnostic medicine research is to estimate and compare the accuracies of diagnostic tests. This book provides a comprehensive account of statistical methods for design and analysis of diagnostic studies, including sample size calculations, estimation of the accuracy of a diagnostic test, comparison of accuracies of competing diagnostic tests, and regression analysis of diagnostic accuracy data. Discussing recently developed methods for correction of verification bias and imperfect reference bias, methods for analysis of clustered diagnostic accuracy data, and meta-analysis methods, Statistical Methods in Diagnostic Medicine explains:
* Common measures of diagnostic accuracy and designs for diagnostic accuracy studies
* Methods of estimation and hypothesis testing of the accuracy of diagnostic tests
* Meta-analysis
* Advanced analytic techniques-including methods for comparing correlated ROC curves in multi-reader studies, correcting verification bias, and correcting when an imperfect gold standard is used
Thoroughly detailed with numerous applications and end-of-chapter problems as well as a related FTP site providing FORTRAN program listings, data sets, and instructional hints, Statistical Methods in Diagnostic Medicine is a valuable addition to the literature of the field, serving as a much-needed guide for both clinicians and advanced students.
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| Customer Reviews:
 comprehensive and rigorous August 18, 2009
Michael R. Chernick (Holland PA)
Another reviewer has compared this book with the one by Pepe but is not aware of the book by Broemeling. I reviewed Broemelings book and have this one so in addition to discussing the features of the Zhou-Obuchowski-McClish book I will make some comments comparing it to Lyle Broemeling's book.
Although this book was published in 2002 it is still very contemporary and useful. Both the classical and Bayesian approaches are covered but the details of Bayesian approaches using MCMC methods is not here so if you are interested in that it is well-covered in Broemeling's book. This book is comprehensive and rigorous and show all the modern techniques including the bootstrap. A published article on a bootstrap approach to a diagnostic testing problem involving a mixed linear model is covered in detail and critiqued for depending on an independence assumption.
What I like most about the are the last two chapters 11 and 12. This is material I have not seen before with chapter 11 showing the types of bias that can occur when the gold standard is imperfect (a very common problem given very thorough answers here). Chapter 12 provides statistical methods for habdling multiple studies for evaluating 1) sensitivity and specificity for a diagnostic test and 2) ROC area estimates ofor a diagnostic test using fixed and random effects models.
Also chapter 6 provides methods for estimating sample size when determining area under ROC curves and sensitivity and specificity for single tests, comparisons of two tests, determining equivalence of two tests and more. Methods are illustrated using real examples.
At a time when biomarkers are starting to be used as diagnostics this methodology becomes extremely important.
 And the winner is... November 4, 2004
StatAge (Europe, EU)
17 out of 17 found this review helpful
There are two modern books in the field. This one by Profs Zhou, Obuchowski, McClish and the book by Prof. Pepe. All four are experts in this field. Both books present the same aspects of statistical diagnostic testing and both can be of invaluable help for researchers (both applied and more academic) and graduate students. However, Professor Pepe has done an excellent job (if I may) using a clear, concise notation and language throughout. On the other hand this book (ZOM) is not that well written, giving more weight in the presentation of the personal research of the authors. As a result there is some notation inconsistency (not too puzzling though) and the flow of the text is not that smooth. Both books have full reference lists, they present interesting applications and give a number of exercises at the end of each chapter.
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