A generalization of Passing-Bablok regression is proposed for comparing multiple measurement methods simultaneously. Possible applications include assay migration studies or interlaboratory trials. When comparing only two methods, the method reduces to the usual Passing-Bablok estimator. It is close in spirit to reduced major axis regression, which is, however, not robust. To obtain a robust estimator, the major axis is replaced by the (hyper-)spherical median axis. The method is shown to reduce to the usual Passing-Bablok estimator if only two methods are compared. This technique has been applied to compare SARS-CoV-2 serological tests, bilirubin in neonates, and an in vitro diagnostic test using different instruments, sample preparations, and reagent lots. In addition, plots similar to the well-known Bland-Altman plots have been developed to represent the variance structure.

翻译：针对同时比较多种测量方法的需求，本文提出了一种泛化的Passing-Bablok回归方法。该方法可应用于检测方法迁移研究或实验室间试验。当仅比较两种方法时，该方法退化为常规的Passing-Bablok估计量。其思路接近降主轴回归（后者不具备稳健性）。为获得稳健估计量，本文用（超）球面中位数轴替代主轴。理论证明，若仅比较两种方法，该方法可简化为常规Passing-Bablok估计量。该技术已应用于SARS-CoV-2血清学检测、新生儿胆红素检测以及采用不同仪器、样本制备方法和试剂批次的体外诊断检测的比较。此外，本文还开发了类似经典Bland-Altman图的图表以呈现方差结构。