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Bücher | Statistical Methods in Diagnostic Medicine
 

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Zhou, Xiao-Hua / Obuchowski, Nancy A. / McClish, Donna K.
Statistical Methods in Diagnostic Medicine
Wiley Series in Probability and Statistics

2. Auflage April 2011
109,- Euro
2011. 592 Seiten, Hardcover
ISBN 978-0-470-18314-4 - John Wiley & Sons

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Kurzbeschreibung
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 the 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. This updated edition features edited case studies and new methods, including screening tests, semi-parametric and non-parametric regression models, and SROC and partial areas. Clinicians and advanced students will benefit from this much-needed guide.

Aus dem Inhalt
List of Figures.

List of Tables.

Preface.

Acknowledgments.

Part 1. Basic Concepts and Methods.

1. Introduction.

1.1 Diagnostic Test Accuracy Studies.

1.2 Case Studies.

1.3 Software.

1.4 Topics Not Covered in This Book.

2. Measures of Diagnostic Accuracy.

2.1 Sensitivity and Specificity.

2.2 Combined Measures of Sensitivity and Specificity.

2.3 Receiver Operating Characteristic (ROC) Curve.

2.4 Area Under the ROC Curves.

2.5 Sensitivity at Fixed FPR.

2.6 Partial Area Under the ROC Curve.

2.7 Likelihood Ratios.

2.8 ROC Analysis When the True Diagnosis is Not Binary.

2.9 C-Statistic and Other Measures to Compare Prediction Models.

2.10 Localization and Detection of Multiple Lesions.

2.11 Positive and Negative Predictive Values, Bayes Theorem, and Case Study 2.

2.12 Optimal Decision Threshold on the ROC Curve.

2.13 Interpreting the Results of Multiple Tests.

3. Design of Diagnostic Accuracy Studies.

3.1 Establish the Objective of the Study.

3.2 Identify the Target Patient Population.

3.3 Select a Sampling Plan for Patients.

3.4 Select the Gold Standard.

3.5 Choose a Measure of Accuracy.

3.6 Identify Target Reader Population.

3.7 Select Sampling Plan for Readers.

3.8 Plan Data Collection.

3.9 Plan Data Analyses.

3.10 Determine Sample Size.

4. Estimation and Hypothesis Testing in a Single Sample.

4.1 Binary-Scale Data.

4.2 Original-Scale Data.

4.3 Continuous-Scale Data.

4.4 Testing the Hypothesis that the ROC Curve Area or Partial Area is a Specific Value.

5. Comparing the Accuracy of Two Diagnostic Tests.

5.1 Binary-Scale Data.

5.2 Original- and Continuous-Scale Data.

5.3 Tests of Equivalence.

6. Sample Size Calculations.

6.1 Studies Estimating the Accuracy of a Single Test.

6.2 Sample Size for Detecting a Di(r)erence in Accuracies of Two Tests.

6.3 Sample Size for Assessing Non-Inferiority or Equivalency of Two Tests.

6.4 Sample Size for Determining a Suitable Cutoff Value.

6.5 Sample Size Determining for Multi-Reader Studies.

6.6 Alternative to Sample Size Formulae.

7. Issues in Meta-analysis for Diagnostic Accuracy Studies.

7.1 Objectives.

7.2 Retrieval of the Literature.

7.3 Inclusion/Exclusion Criteria.

7.4 Extracting Information from the Literature.

7.5 Statistical Analysis.

7.6 Public Presentation.

Part II. Advanced Methods.

8. Regression Analysis for Independent ROC Data.

8.1 Four Clinical Studies.

8.2 Regression Models for Continuous-Scale Tests.

8.3 Regression Models for Ordinal-Scale Tests.

9. Analysis of Multiple Reader and/or Multiple Test Studies.

9.1 Studies Comparing Multiple Tests with Covariates.

9.2 Studies with Multiple Reader and Multiple Tests.

9.3 Analysis of Multiple Tests Designed to Locate and Diagnose Lesions.

10. Methods for Correcting Verification Bias.

10.1 Examples.

10.2 Impact of Verification Bias.

10.3 A Single Binary-Scale Test.

10.4 Correlated Binary-Scale Tests.

10.5 A Single Ordinal-Scale Test.

10.6 Correlated Ordinal-Scale Tests.

10.7 Continuous-Scale Tests.

11. Methods for Correcting Imperfect Gold Standard Bias.

11.1 Examples.

11.2 Impact of Imperfect Gold Standard Bias.

11.3 One Single Binary Test in a Single Population.

11.4 One Single Binary Test in G Populations.

11.5 Multiple Binary Tests in One Single Population.

11.6 Multiple Binary Tests in G Populations.

11.7 Multiple Ordinal-Scale Tests in One Single Population.

11.8 Multiple Tests in One Single Population.

12. Statistical Analysis for Meta-analysis.

12.1 Binary-Scale Data.

12.2 Ordinal-or Continuous-Scale Data.

12.3 ROC Curve Area.

Appendix A: Case Studies and Chapter 8 Data.

Appendix B: Jackknife and Bootstrap Methods of Estimating Variances and Confidence Intervals. Nam

 




 

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