Short description It is difficult for medics and biostatisticians comparing two different methods of measuring to ascertain if either method is giving the true value of the quantity being measured. Comparing Clinical Measurement Methods provides the practical tools for analyzing method comparison studies along with guidance on what to report and how to plan comparison studies. Author Bendix Carstensen, an esteemed expert on the subject, presents a modeling framework that allows biostatisticians, clinicians, medical researchers, and practitioners to analyze clinical data and compare measurements taken from different clinical centers using different methods.
From the contents Acknowledgments.
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 use 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 Howto. . . .
3.1 . . . 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 transformation.
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.
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.
8.4 Several methods.
8.5 Variance components.
8.6 Summary.
9 Repeatability, reproducibility and coefficient of variation.
