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.

摘要

统计分析有两种思想流派，常客体和贝叶斯学。尽管在大样本研究中这两种方法产生相似的估计和预测，但它们的解释是不同的。Bland Altman分析是一种统计方法，广泛用于比较两种测量方法。它最初是在一个频繁主义者的框架下提出的，尽管贝叶斯分析越来越流行，但它并没有在贝叶斯框架下使用。看起来，数学和计算复杂性使使用贝叶斯Bland Altman分析的方法变窄了。在本文中，我们提供了贝叶斯Bland Altman分析的教程。我们建议的一种方法是通过后验预测分布来解决Bland Altman分析的目的。先验）两次未来测量之间的差异。为了减轻数学和计算复杂性，为接口小程序提供了指南。