Agreement coefficients for continuous variables: A review

TL;DR

This review comprehensively covers statistical methods for assessing agreement between continuous variables, emphasizing recent developments, extensions, and applications in modern fields like image analysis and environmental statistics.

Contribution

It provides an updated synthesis of agreement coefficients, including probabilistic and spatial generalizations, highlighting their evolution, connections, and future research directions.

Findings

Discusses extensions to robust, multivariate, and repeated-measures settings.

Highlights recent developments like probability of agreement and alternative distance measures.

Includes illustrative examples and comparative discussions of existing methods.

Abstract

Agreement coefficients provide a fundamental framework for quantifying the concordance between two or more measurement methods applied to the same continuous variable. Unlike correlation, which measures the strength of a linear relationship, agreement focuses on assessing whether measurements are numerically similar, capturing both precision and accuracy. This review provides a comprehensive overview of the primary statistical approaches for assessing agreement between continuous variables. Such a synthesis is timely, as it has been 15-20 years since the last major review in the field. Beginning with the seminal contributions of Bland and Altman (1986) and Lin (1989), the paper discusses extensions of their methods to robust, multivariate, and repeated-measures settings, as well as recent developments like the probability of agreement and measures based on alternative distance functions measures. Special attention is given to probabilistic and spatial generalizations, including frameworks designed for geostatistical and areal data, which have become increasingly relevant in modern applications such as image analysis and environmental statistics. Through illustrative examples and comparative discussions, this review highlights the evolution, connections, and limitations of existing agreement measures, identifying open challenges and directions for future research.