A Tutorial of Bland Altman Analysis in a Bayesian Framework

Autor/inn/en	Alari, Krissina M.; Kim, Steven B.; Wand, Jeffrey O.
Titel	A Tutorial of Bland Altman Analysis in a Bayesian Framework
Quelle	In: Measurement in Physical Education and Exercise Science, 25 (2021) 2, S.137-148 (12 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1091-367X
DOI	10.1080/1091367X.2020.1853130
Schlagwörter	Statistical Analysis; Bayesian Statistics; Measurement; Probability + Suchen Sie Ihr Suchwort? Statistische Analyse; Messverfahren; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie
Abstract	There are two schools of thought in statistical analysis, frequentist, and Bayesian. Though the two approaches produce similar estimations and predictions in large-sample studies, their interpretations are different. Bland Altman analysis is a statistical method that is widely used for comparing two methods of measurement. It was originally proposed under a frequentist framework, and it has not been used under a Bayesian framework despite the growing popularity of Bayesian analysis. It seems that the mathematical and computational complexity narrows access to Bayesian Bland Altman analysis. In this article, we provide a tutorial of Bayesian Bland Altman analysis. One approach we suggest is to address the objective of Bland Altman analysis via the posterior predictive distribution. We can estimate the probability of an acceptable degree of disagreement (fixed "a priori") for the difference between two future measurements. To ease mathematical and computational complexity, an interface applet is provided with a guideline. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01