Exploratory method comparison analysis with emphasis on graphical illustrations

<b>Objectives:</b> To develop and present simple visual and descriptive summary measures of agreement in method comparison studies with replicated measurements and to discuss detection of drift in method comparison studies. Summary measures may serve as an exploratory data analysis guiding further agreement and decision analysis of two methods using the Bland and Altman method and mixed-effects modeling. <b>Materials and methods:</b> The methodological approach is illustrated using freely available clinical datasets from two published method comparison studies with repeated measurements on each subject. <b>Results:</b> With the use of ellipses and a numerical ideality index as summary measures for each subject with paired measurements from two clinical methods, it is possible to quickly decode a dataset's intra- and interindividual variation, differential and proportional bias, possible drift, and the number of measured subjects in clinically relevant areas for the two methods. <b>Conclusion:</b> Simple and intuitive exploratory method comparison analysis can be performed and interpreted even for relatively large datasets prior to more advanced statistical analysis of method comparisons using data with replicated measurements.