Statistical Methods in Diagnostic Medicine / Wiley Series in Probability and Statistics (ePub)

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.