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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

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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.

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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.