Revised Passing-Bablok Regression Method for Model Comparison

Abstract

Type-II regression models are used to compare more than one method that makes the same measurement. The Passing-Bablok regression method, which is one of them, is non-parametric and can yield more successful results than other comparison methods, particularly when there are outliers. In this study, innovations in the calculation of the slope and intercept parameters used in the traditional Passing-Bablok method are proposed. Instead of the median parameter used in the classical model, the use of the trimean parameter is suggested, and the model parameter estimates are adjusted accordingly. The proposed model and classical model predictions were compared on 15 different datasets, eight of which were simulations. It was determined that the proposed model calculations contained fewer errors than the results of the classical method.