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A Tutorial of Bland Altman Analysis in A Bayesian Framework
Krissina M Alari1, Steven B Kim1, Jeffrey O Wand1
1Department of Mathematics and Statistics, California State University, Monterey Bay, Seaside, California, USA.
Measurement in Physical Education and Exercise Science
|May 21, 2021
Summary
This tutorial introduces Bayesian Bland Altman analysis for comparing measurement methods. It simplifies complex calculations, enabling probability estimation of acceptable disagreement between future measurements.
Area of Science:
- Statistics
- Biostatistics
- Medical Statistics
Background:
- Two primary statistical analysis schools exist: frequentist and Bayesian.
- Bland Altman analysis, a frequentist method for comparing measurement agreement, lacks Bayesian application despite Bayesian analysis popularity.
- Complexity hinders Bayesian Bland Altman analysis adoption.
Purpose of the Study:
- To provide a tutorial on Bayesian Bland Altman analysis.
- To simplify the application of Bayesian methods for measurement comparison.
- To enable estimation of the probability of acceptable disagreement between future measurements.
Main Methods:
- Utilizing the posterior predictive distribution to address Bland Altman analysis objectives.
- Developing an interface applet to mitigate mathematical and computational complexity.
- Providing guidelines for practical implementation.
Main Results:
- Demonstrates a method to perform Bayesian Bland Altman analysis.
- Facilitates the estimation of the probability of acceptable disagreement for future measurements.
- Offers a user-friendly tool to overcome computational barriers.
Conclusions:
- Bayesian Bland Altman analysis is feasible and offers valuable insights.
- The provided tutorial and applet enhance accessibility to Bayesian measurement comparison.
- This approach can improve the understanding of measurement agreement in various scientific fields.
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