(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

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.