Estimation of Bias between 2 Analytical Methods at Clinically Important Ranges

Abstract

An approach for estimating bias between 2 analytical methods at different clinical ranges is introduced in this article. The approach models replicated data obtained from the reference and the test method in terms of repeatability and trueness bias. The latter can be partitioned into constant and proportional bias. The approach is based on maximum likelihood estimation and can accommodate normal as well as Poisson and binomial distributions that apply to hematology applications and/or other laboratory methods that count particles per unit of volume and/or time. A full spectrum of statistical inference in the form of confidence intervals for each estimate as well as any statistical hypothesis testing is provided. At the same time these estimates can be practically interpreted and related to any clinical important range or decision point. We recommend this approach as an alternative to the National Committee for Clinical Laboratory Standards (NCCLS) EP9-A2 approach in cases where the application of the NCCLS standard is not appropriate.