Evaluation of Agreement between Measurement Methods from Data with Matched Repeated Measurements via the Coefficient of Individual Agreement

• Authors: Michael J Haber, Emory University; Jingjing Gao, Emory University; Huiman X Barnhart, Duke University
• Journal Title: Journal of Data Science
• Volume: Volume 8, Number 3
• Publisher: Columbia University, New York | 2010-07-01, Pages 457-469
• Type of Work: Article | Post-print: After Peer Review
• Subjects: Biology, Biostatistics; Biology, Bioinformatics; Health Sciences, Public Health
• Keywords: coefficient of individual agreement; method comparisons; repeated measurements

Abstract

Summary We propose a simple method for evaluating agreement between methods of measurement when the measured variable is continuous and the data consists of matched repeated observations made with the same method under different conditions. The conditions may represent different time points, raters, laboratories, treatments, etc. Our approach allows the values of the measured variable and the magnitude of disagreement to vary across the conditions. The coefficient of individual agreement (CIA), which is based on the comparison of the between and within-methods mean squared deviation (MSD) is used to quantify the magnitude of agreement between measurement methods. The new approach is illustrated via two examples from studies designed to compare (a) methods of evaluating carotid stenosis and (b) methods of measuring percent body fat.