Assessing agreement between two measurement systems: An alternative to the limits of agreement approach.
The comparison of two measurement systems is important in medical and other contexts. A common goal is to decide if a new measurement system agrees suitably with an existing one, and hence whether the two can be used interchangeably. Various methods for assessing interchangeability are available, the most popular being the limits of agreement approach due to Bland and Altman. In this article, we review the challenges of this technique and propose a model-based framework for comparing measurement systems that overcomes those challenges. The proposal is based on a simple metric, the probability of agreement, and a corresponding plot which can be used to summarize the agreement between two measurement systems. We also make recommendations for a study design that facilitates accurate and precise estimation of the probability of agreement.
Business and Industrial Statistics Research Group, Department of Statistics and Actuarial Science, University of Waterloo, Canada.
Nathaniel T
NT
Stevens
Business and Industrial Statistics Research Group, Department of Statistics and Actuarial Science, University of Waterloo, Canada.
Stefan H
SH
Steiner
Business and Industrial Statistics Research Group, Department of Statistics and Actuarial Science, University of Waterloo, Canada.
R Jock
RJ
MacKay
D015982:Bias; D056808:Biostatistics / Q000379:methods*; D001795:Blood Pressure Determination / Q000706:statistics & numerical data; D001921:Brain / Q000000981:diagnostic imaging; D002138:Calibration; D002552:Cerebral Ventricles / Q000000981:diagnostic imaging; D003198:Computer Simulation; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D011336:Probability; D015203:Reproducibility of Results; D018401:Sample Size
Bias; homoscedasticity; interchangeability; measurement error; probability of agreement; repeatability