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Ebook Statistical Methods in Diagnostic Medicine, by Xiao-Hua Zhou, Nancy A. Obuchowski, Donna K. McClish
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Praise for the First Edition
" . . . the book is a valuable addition to the literature in the field, serving as a much-needed guide for both clinicians and advanced students."—Zentralblatt MATH
A new edition of the cutting-edge guide to diagnostic tests in medical research
In recent years, a considerable amount of research has focused on evolving methods for designing and analyzing diagnostic accuracy studies. Statistical Methods in Diagnostic Medicine, Second Edition continues to provide a comprehensive approach to the topic, guiding readers through the necessary practices for understanding these studies and generalizing the results to patient populations.
Following a basic introduction to measuring test accuracy and study design, the authors successfully define various measures of diagnostic accuracy, describe strategies for designing diagnostic accuracy studies, and present key statistical methods for estimating and comparing test accuracy. Topics new to the Second Edition include:
-
Methods for tests designed to detect and locate lesions
-
Recommendations for covariate-adjustment
-
Methods for estimating and comparing predictive values and sample size calculations
-
Correcting techniques for verification and imperfect standard biases
-
Sample size calculation for multiple reader studies when pilot data are available
-
Updated meta-analysis methods, now incorporating random effects
Three case studies thoroughly showcase some of the questions and statistical issues that arise in diagnostic medicine, with all associated data provided in detailed appendices. A related web site features Fortran, SAS�, and R software packages so that readers can conduct their own analyses.
Statistical Methods in Diagnostic Medicine, Second Edition is an excellent supplement for biostatistics courses at the graduate level. It also serves as a valuable reference for clinicians and researchers working in the fields of medicine, epidemiology, and biostatistics.
- Sales Rank: #1075485 in Books
- Published on: 2011-03-29
- Original language: English
- Number of items: 1
- Dimensions: 9.60" h x 1.40" w x 6.50" l, 2.15 pounds
- Binding: Hardcover
- 592 pages
Review
"The authors, overall, have done a good job of revising their first edition, addressing the critical reviews as well as expanding and updating their coverage . . . In summary, this is a good book, focusing on medical diagnosis as the name promises, presenting a wealth of methods in detail with good discussion." (Journal of Biopharmaceutical Statistics, 2011)
"Early chapters are accessible to readers with a basic knowledge of statistical and medical terminology, and the second section addresses data analysts with basic training in biostatistics. Later chapters assume deeper background in statistics, but the examples should be accessible to all. The 2002 edition has been updated throughout, and three new case studies have been added." (Booknews, 1 June 2011)
From the Back Cover
Praise for the First Edition
" . . . the book is a valuable addition to the literature in the field, serving as a much-needed guide for both clinicians and advanced students."—Zentralblatt MATH
A new edition of the cutting-edge guide to diagnostic tests in medical research
In recent years, a considerable amount of research has focused on evolving methods for designing and analyzing diagnostic accuracy studies. Statistical Methods in Diagnostic Medicine, Second Edition continues to provide a comprehensive approach to the topic, guiding readers through the necessary practices for understanding these studies and generalizing the results to patient populations.
Following a basic introduction to measuring test accuracy and study design, the authors successfully define various measures of diagnostic accuracy, describe strategies for designing diagnostic accuracy studies, and present key statistical methods for estimating and comparing test accuracy. Topics new to the Second Edition include:
- Methods for tests designed to detect and locate lesions
- Recommendations for covariate-adjustment
- Methods for estimating and comparing predictive values and sample size calculations
- Correcting techniques for verification and imperfect standard biases
- Sample size calculation for multiple reader studies when pilot data are available
- Updated meta-analysis methods, now incorporating random effects
Three case studies thoroughly showcase some of the questions and statistical issues that arise in diagnostic medicine, with all associated data provided in detailed appendices. A related web site features Fortran, SAS�, and R software packages so that readers can conduct their own analyses.
Statistical Methods in Diagnostic Medicine, Second Edition is an excellent supplement for biostatistics courses at the graduate level. It also serves as a valuable reference for clinicians and researchers working in the fields of medicine, epidemiology, and biostatistics.
About the Author
Xiao-Hua Zhou, PhD, is Professor of Biostatistics at the University of Washington and Director and Research Career Scientist at the Biostatistics Unit of the Veterans Affairs Puget Sound Healthcare System. He is a Fellow of the American Statistical Association and the author of more than 100 published articles on statistical methods in diagnostic medicine and causal inferences.
Nancy A. Obuchowski, PhD, is Vice Chairperson of the Department of Quantitative Health Sciences at the Cleveland Clinic Foundation. A Fellow of the American Statistical Association, she has written more than 100 journal articles on the design and analysis of studies of screening and diagnostic tests.
Donna K. McClish, PhD, is Associate Professor and Graduate Program Director in Biostatistics at Virginia Commonwealth University. She has written more than 100 journal articles on statistical methods in epidemiology, diagnostic medicine, and health services research.
Most helpful customer reviews
23 of 24 people found the following review helpful.
And the winner is...
By StatAge
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.
4 of 5 people found the following review helpful.
comprehensive and rigorous
By Michael R. Chernick
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.
0 of 0 people found the following review helpful.
Mandatory reading for clinical research on screening
By MargaretNC
I ordered this book along with Pepe's text in 2006, shortly after completing a clinical research fellowship in epidemiology. The two books together provide a strong basis for research on screening tools and risk assessment. Clinical research fellows and junior investigators who plan to study screening need to read this book and practice diagnostic accuracy analysis because it will teach you universal skills in evaluation and interpretation of studies of screening. The two diagnostic accuracy analyses I have published were part of the pilot data for my first of 3 NIH grants, so the material you learn from this book will also inform grants.
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