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Is the Bland-Altman plot method useful without inferences for accuracy, precision, and agreement?
Paulo Sergio Panse Silveira1, Joaquim Edson Vieira2, José de Oliveira Siqueira1
1Universidade de São Paulo. Faculdade de Medicina. Departamento de Patologia. São Paulo, SP, Brasil.
Revista De Saude Publica
|February 21, 2024
Summary
This study introduces a novel three-step statistical framework as an alternative to the Bland-Altman plot for assessing measurement technique equivalence, enhancing objectivity and identifying sources of error.
Area of Science:
- Biostatistics
- Measurement Science
- Statistical Modeling
Background:
- The Bland-Altman plot is widely used for assessing agreement between measurement techniques but often misinterpreted due to a lack of robust inferential statistics.
- Existing alternatives like Pearson's correlation or linear regression do not adequately identify weaknesses in measurement techniques.
Purpose of the Study:
- To propose a comprehensive statistical framework as an alternative to the Bland-Altman plot for evaluating measurement technique equivalence.
- To introduce an innovative three-step approach for assessing accuracy, precision, and agreement between techniques, enhancing objectivity.
- To develop a user-friendly R package for efficient analysis and interpretation of technique equivalences.
Main Methods:
- A three-step nested inferential statistical approach based on structural regressions was developed.
- The method assesses equivalence of structural means (accuracy), structural variances (precision), and concordance with the structural bisector line (agreement).
- Analytical methods and a robust bootstrapping approach were employed, complemented by graphical outputs aligned with Bland-Altman principles.
Main Results:
- The proposed method was validated using five datasets from studies that employed the Bland-Altman method.
- Analysis revealed one case of strict equivalence, three cases of partial equivalence, and one case of poor equivalence.
- An R package with open codes and data is freely available for researchers.
Conclusions:
- The Bland-Altman plot method, despite its communication ease, is frequently misinterpreted due to insufficient inferential statistical support.
- The proposed method preserves graphical communication principles while incorporating robust inferential statistics for equivalence testing.
- Decomposing equivalence into accuracy, precision, and agreement aids in pinpointing issues when developing new measurement techniques.
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