| Description |
1 online resource (xi, 157 pages) : illustrations (some color) |
| Series |
Statistics in Practice |
|
Statistics in practice.
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| Contents |
1. Introduction -- 2. Method comparisons -- 3. How to ... -- 4. Two methods with a single measurement on each -- 5. Replicate measurements -- 6. Several methods of measurement -- 7. A general model for method comparisons -- 8. Transformation of measurements -- 9. Repeatability, reproducibility and coefficient of variation -- 10. Measures of association and agreement -- 11. Design of method comparison studies -- 12. Examples using standard software -- 13. The MethComp package for R -- 14. References -- 15. Index -- 16. Statistics in practice |
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(Publisher-supplied data) 1 Introduction -- 2 Method comparisons -- 2.1 One measurement by each method -- 2.1.1 Prediction of one method from another -- 2.1.2 Why not the correlation? -- 2.1.3 A new method and a reference method -- 2.2 Replicate measurements by each method -- 2.2.1 Exchangeable replicates: fat data -- 2.2.2 Linked replicates: Oximetry data -- 2.2.3 Why not use the averages of the replicates? -- 2.3 More than two methods -- 2.4 Terminology and notation -- 2.5 What it is all about -- 3 How to use this chapter -- 3.2 Two methods -- 3.2.1 Single measurements -- 3.2.2 Comparing with a gold standard -- 3.2.3 Replicate measurements -- 3.3 More than two methods -- 3.3.1 Single measurements -- 3.3.2 Replicate measurements -- 4 Two methods with a single measurement on each -- 4.1 Model for limits of agreement -- 4.1.1 Prediction between methods -- 4.1.2 The correlation of the difference and the average -- 4.2 Non-constant difference between methods -- 4.3 A worked example -- 4.4 What really goes on -- 4.4.1 Scaling -- 4.4.2 Independence -- 4.4.3 Actual behavior -- 4.5 Other regression methods for non-constant bias -- 4.5.1 Why ordinary regression fails -- 4.5.2 Deming regression -- 4.6 Comparison with a gold standard -- 4.7 Non-constant variance -- 4.7.1 Regression approach -- 4.7.2 A worked example -- 4.8 Transformations -- 4.8.1 Log-transform -- 4.9 Summary -- 5 Replicate measurements -- 5.1 Pairing of replicate measurements -- 5.1.1 Exchangeable replicates -- 5.1.2 Linked replicates -- 5.2 Plotting replicate measurements -- 5.3 Models for replicate measurements -- 5.3.1 Exchangeable replicates -- 5.3.2 Linked replicates -- 5.4 Interpretation of the random effects -- 5.5 Estimation -- 5.6 Getting it wrong and getting it almost right -- 5.6.1 Averaging over replicates -- 5.6.2 Replicates as items -- 5.7 Summary -- 6 Several methods of measurement -- 6.1 Model -- 6.2 Replicate measurements -- 6.3 Single measurement by each method |
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7 A general model for method comparisons -- 7.1 Scaling -- 7.2 Interpretation of the random effects -- 7.3 Parametrization of the mean -- 7.4 Prediction limits -- 7.4.1 Mean of replicates -- 7.4.2 Plotting predictions between methods -- 7.4.3 Reporting variance components -- 7.4.4 Comparison with a gold standard -- 7.5 Estimation -- 7.5.1 Alternating regressions -- 7.5.2 Estimation using BUGS -- 7.5.3 A worked example -- 7.6 Models with non-constant variance -- 7.6.1 Linear dependence of residual standard error -- 7.7 Summary -- 8 Transformation of measurements -- 8.1 Log-transformation -- 8.2 Transformations of percentages -- 8.2.1 A worked example -- 8.2.2 Implementation in MethComp -- 8.3 Other transformations -- 8.3.1 Different transformations for different methods -- 8.4 Several methods -- 8.5 Variance components -- 8.6 Summary -- 9 Repeatability, reproducibility and coefficient of variation -- 9.1 Repeatability -- 9.2 Reproducibility -- 9.3 Coefficient of variation -- 9.3.1 Symmetric interval on the log-scale -- 9.3.2 Computing the CV correctly -- 9.3.3 Transformations -- 10 Measures of association and agreement -- 10.1 IBC individual bioequivalence criterion -- 10.2 Agreement index -- 10.3 Relative variance index -- 10.4 Total deviation index -- 10.5 Correlation measures -- 10.5.1 Correlation coefficient -- 10.5.2 Intraclass correlation coefficient -- 10.5.3 Concordance correlation coefficient -- 10.6 Summary -- 11 Design of method comparison studies -- 11.1 Sample size -- 11.1.1 Mean parameters -- 11.1.2 Variance parameters -- 11.2 Repeated measures designs -- 11.3 Summary -- 12 Examples using standard software -- 12.1 SAS -- 12.1.1 Exchangeable replicates -- 12.1.2 Linked replicates -- 12.2 Stata -- 12.2.1 Exchangeable replicates -- 12.2.2 Linked replicates -- 12.3 R 12.3.1 Exchangeable replicates -- 12.3.2 Linked replicates -- 13 The MethComp package for R -- 13.1 Data structures -- 13.2 Function overview -- 13.2.1 Graphical functions -- 13.2.2 Data manipulating functions -- 13.2.3 Analysis functions -- 13.2.4 Reporting functions |
| Summary |
"This book sets out to provide an example-based, 'how-to' guide to the comparison of measurement methods in a clinical context. Whilst much material has been published on obtaining and comparing accurate measurements in medical research this will be the first book length treatment of the subject. The author draws upon his experience in multicentre clinical studies to present data and examples drawn from real case studies. The book will be supplemented by a website hosting datasets and programs to allow the reader to reproduce all of the analyses"--Provided by publisher |
| Bibliography |
Includes bibliographical references and index |
| Notes |
English |
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Print version record |
| Subject |
Clinical trials -- Evaluation
|
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Clinical trials -- Statistical methods
|
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Clinical medicine.
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Case-control method.
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Regression analysis.
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Clinical Medicine
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Case-Control Studies
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Models, Statistical
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Regression Analysis
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Statistics as Topic -- methods
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MEDICAL -- Laboratory Medicine.
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Regression analysis
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Clinical medicine
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Case-control method
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Clinical trials -- Evaluation
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Clinical trials -- Statistical methods
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| Form |
Electronic book
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| LC no. |
2010010826 |
| ISBN |
9780470683019 |
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0470683015 |
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9780470683002 |
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0470683007 |
|
1119957540 |
|
9781119957546 |
|
9786612653896 |
|
6612653892 |
|
