An Information Criterion Approach for Assessing Agreement When Comparing Two Methods of Measurement

In laboratory and clinical sciences, it is a common enough challenge to compare two methods of measurement on the same set of samples or closely related samples with the goal of assessing agreement. Current regulatory guidance cites the Bland-Altman plot, Deming regression, and concordance correlation coefficient. Each choice relies on its assumption of a particular model. A new statistical approach based on an information criterion is proposed. This integrated approach evaluates the data against six models simultaneously. This information criterion approach provides an objective, data-driven, easily calculated, informative, and clear decision rule. Real data sets from the assay comparison of patient-centric sampling are used to illustrate the new approach.