The comparison of methods of measurement is a common problem in clinical practice; as novel methods are developed, establishing their agreement with existing methods is crucial. The probability of agreement (PoA) has previously been proposed as an intuitive and informative means of assessing agreement between two methods of measurement. It straightforwardly quantifies the likelihood that two measurements by different methods on the same subject are clinically indistinguishable. In this paper, we overhaul and extend the PoA methodology by developing an inference framework that relaxes several restrictive assumptions made in previous implementations, ultimately increasing its utility in a wider range of applications. We illustrate this more flexible methodology in an example that compares methods of measuring total Prostatic Specific Antigen (tPSA). And we thoroughly investigate its performance via simulation. This work dramatically increases the flexibility, availability, and hence impact of the PoA approach for method comparison.

翻译：测量方法的比较是临床实践中的常见问题；随着新方法的开发，确定它们与现有方法的一致性至关重要。一致性概率（PoA）先前已被提出作为一种直观且信息丰富的手段，用于评估两种测量方法之间的一致性。它直接量化了不同方法对同一受试者进行的两次测量在临床上难以区分的可能性。在本文中，我们通过开发一个推断框架来全面改革并扩展PoA方法论，该框架放宽了先前实现中的若干限制性假设，最终提升了其在更广泛应用中的实用性。我们通过一个比较总前列腺特异性抗原（tPSA）测量方法的示例来阐明这种更灵活的方法论，并通过模拟全面研究其性能。这项工作极大提高了PoA方法在方法比较中的灵活性、可用性，从而增强了其影响力。