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Comparing clinical measurement methods : a practical guide

Author: Bendix Carstensen
Publisher: Chichester, West Sussex : John Wiley & Sons, 2010.
Series: Statistics in practice.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:

* Presents a modeling framework in which biostatisticians cananalyze clinical data and compare measurements taken from differentclinical centres using different methods. * Provides the practical  Read more...

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Genre/Form: Electronic books
Additional Physical Format: Print version:
Carstensen, Bendix.
Comparing clinical measurement methods.
Chichester, West Sussex : John Wiley & Sons, 2010
(DLC) 2010010826
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Bendix Carstensen
OCLC Number: 738752140
Description: 1 online resource (xi, 157, [4] pages).
Contents: Acknowledgments. <p>1 Introduction. <p>2 Method comparisons. <p>2.1 One measurement by each method. <p>2.1.1 Prediction of one method from another. <p>2.1.2 Why not use the correlation? <p>2.1.3 A new method and a reference method. <p>2.2 Replicate measurements by each method. <p>2.2.1 Exchangeable replicates: fat data. <p>2.2.2 Linked replicates: oximetry data. <p>2.2.3 Why not use the averages of the replicates? <p>2.3 More than two methods. <p>2.4 Terminology and notation. <p>2.5 What it is all about. <p>3 How to <p>3.1 use this chapter. <p>3.2 Two methods. <p>3.2.1 Single measurements. <p>3.2.2 Comparing with a gold standard. <p>3.2.3 Replicate measurements. <p>3.3 More than two methods. <p>3.3.1 Single measurements. <p>3.3.2 Replicate measurements. <p>4 Two methods with a single measurement on each. <p>4.1 Model for limits of agreement. <p>4.1.1 Prediction between methods. <p>4.1.2 The correlation of the difference and the average. <p>4.2 Non-constant difference between methods. <p>4.3 A worked example. <p>4.4 What really goes on. <p>4.4.1 Scaling. <p>4.4.2 Independence. <p>4.4.3 Actual behavior. <p>4.5 Other regression methods for non-constant bias. <p>4.5.1 Why ordinary regression fails. <p>4.5.2 Deming regression. <p>4.6 Comparison with a gold standard. <p>4.7 Non-constant variance. <p>4.7.1 Regression approach. <p>4.7.2 A worked example. <p>4.8 Transformations. <p>4.8.1 Log transformation. <p>4.9 Summary. <p>5 Replicate measurements. <p>5.1 Pairing of replicate measurements. <p>5.1.1 Exchangeable replicates. <p>5.1.2 Linked replicates. <p>5.2 Plotting replicate measurements. <p>5.3 Models for replicate measurements. <p>5.3.1 Exchangeable replicates. <p>5.3.2 Linked replicates. <p>5.4 Interpretation of the random effects. <p>5.5 Estimation. <p>5.6 Getting it wrong and getting it almost right. <p>5.6.1 Averaging over replicates. <p>5.6.2 Replicates as items. <p>5.7 Summary. <p>6 Several methods of measurement. <p>6.1 Model. <p>6.2 Replicate measurements. <p>6.3 Single measurement by each method. <p>7 A general model for method comparisons. <p>7.1 Scaling. <p>7.2 Interpretation of the random effects. <p>7.3 Parametrization of the mean. <p>7.4 Prediction limits. <p>7.4.1 Mean of replicates. <p>7.4.2 Plotting predictions between methods. <p>7.4.3 Reporting variance components. <p>7.4.4 Comparison with a gold standard. <p>7.5 Estimation. <p>7.5.1 Alternating regressions. <p>7.5.2 Estimation using BUGS. <p>7.5.3 A worked example. <p>7.6 Models with non-constant variance. <p>7.6.1 Linear dependence of residual standard error. <p>7.7 Summary. <p>8 Transformation of measurements. <p>8.1 Log transformation. <p>8.2 Transformations of percentages. <p>8.2.1 A worked example. <p>8.2.2 Implementation in MethComp. <p>8.3 Other transformations. <p>8.4 Several methods. <p>8.5 Variance components. <p>8.6 Summary. <p>9 Repeatability, reproducibility and coefficient ofvariation. <p>9.1 Repeatability. <p>9.2 Reproducibility. <p>9.3 Coefficient of variation. <p>9.3.1 Symmetric interval on the log scale. <p>9.3.2 Computing the CV correctly. <p>9.3.3 Transformations. <p>10 Measures of association and agreement. <p>10.1 Individual bioequivalence criterion. <p>10.2 Agreement index. <p>10.3 Relative variance index. <p>10.4 Total deviation index. <p>10.5 Correlation measures. <p>10.5.1 Correlation coefficient. <p>10.5.2 Intraclass correlation coefficient. <p>10.5.3 Concordance correlation coefficient. <p>10.6 Summary. <p>11 Design of method comparison studies. <p>11.1 Sample size. <p>11.1.1 Mean parameters. <p>11.1.2 Variance parameters. <p>11.2 Repeated measures designs. <p>11.3 Summary. <p>12 Examples using standard software. <p>12.1 SAS. <p>12.1.1 Exchangeable replicates. <p>12.1.2 Linked replicates. <p>12.2 Stata. <p>12.2.1 Exchangeable replicates. <p>12.2.2 Linked replicates. <p>12.3 R. <p>12.3.1 Exchangeable replicates. <p>12.3.2 Linked replicates. <p>13 The MethComp package for R. <p>13.1 Data structures. <p>13.2 Function overview. <p>13.2.1 Graphical functions. <p>13.2.2 Data manipulating functions. <p>13.2.3 Analysis functions. <p>13.2.4 Reporting functions. <p>References. <p>Index.
Series Title: Statistics in practice.
Responsibility: Bendix Carstensen.

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