Correlation does not imply agreement: A cautionary tale for researchers and reviewers

Correlation does not imply agreement: A cautionary tale for researchers and reviewers

REVIEWED BY Assoc Prof Tristan Reddan, FASA | ASA SIG: Research

REFERENCE | Authors: Edwards C, Allen H & Chamunyonga C

WHY THE STUDY WAS PERFORMED

The study was performed to clarify the terms ‘correlation’ and ‘agreement’ and their appropriate use in sonography research. The authors aimed to address common pitfalls and inconsistencies in reporting these statistical tests in the literature. The study’s relevance to sonographers and reviewers is evident, as it aims to improve the quality of research and reduce inconsistencies in the field. By providing clarity on the proper use of these statistical methods, the study seeks to benefit researchers conducting studies comparing measurements and reviewers evaluating manuscripts to ensure the methodology used is sufficient to justify the claims.

HOW THE STUDY WAS PERFORMED

The study was conducted as a comprehensive review of fundamental biostatistics and common statistical methods used for continuous variables in sonography research. The authors provided a detailed explanation of the terms ‘correlation’ and ‘agreement’ and outlined the statistical tests used to assess correlation, highlighting common pitfalls authors fall into when reporting these tests. Examples of inaccurate use of correlation tests in the sonography literature were presented and the authors recommended alternative methods for assessing agreement between measurements. The study included plots created in the R statistical software package and a supplementary data file was provided for readers to perform similar statistical tests.

WHAT THE STUDY FOUND

The study found that correlation and agreement are often misused in sonography research, with correlation coefficients being incorrectly applied to assess agreement between measurements. The authors demonstrated that two highly correlated variables may not necessarily agree, and visual inspection of scatter plots is crucial to avoid incorrect assumptions. The study highlighted situations where the Pearson correlation coefficient should not be used, such as in the presence of outliers, heteroscedasticity, clustered data, or non-linear relationships. The authors emphasised the importance of plotting the relationship between variables of interest on a scatter plot to avoid incorrect assumptions and to determine the nature of the correlation (linear or non-linear). The study recommended alternative methods for assessing agreement between continuous measurements, such as the intra-class correlation coefficient (ICC) and BlandAltman plots with limits of agreement. Examples from the sonography literature were provided to illustrate the misuse of correlation coefficients in assessing agreement between measurements or imaging techniques, such as comparing standard 2D and panoramic imaging measurements or evaluating an image review scoring system.

The authors demonstrated that two highly correlated variables may not necessarily agree, and visual inspection of scatter plots is crucial to avoid incorrect assumptions.

RELEVANCE TO CLINICAL PRACTICE

The study’s findings are highly relevant to sonography practice as they emphasise the importance of using appropriate statistical methods to assess agreement between measurements or techniques. Sonographers and researchers should be aware of the limitations of correlation coefficients and the potential for misinterpretation when assessing agreement. The recommended alternative methods, such as ICC and Bland-Altman plots, can be applied to various clinical scenarios in sonography, such as comparing different imaging modes, evaluating interobserver variability, or assessing the reproducibility of measurements under different conditions. Adopting these methods will improve the quality of sonography research, leading to more reliable and valid conclusions that can inform clinical practice, decision-making, and the development of guidelines and protocols. By understanding the proper use of statistical methods for assessing correlation and agreement, sonographers and researchers can design more robust studies and draw accurate conclusions that ultimately benefit patient care.