Matrix mismatch and its estimation in single-lab studies

Abstract

Background: Matrix mismatch arises when the matrix of the test sample differs from the calibration or standard matrix. Matrix mismatch often accounts for a large part of between-laboratory variation. Notwithstanding, it is seldom characterized in method validation studies. Methods: Matrix-mismatch manifests itself as the variation of bias across matrices and has two components: the variation of method bias and the variation of laboratory bias across matrices. The laboratory bias component of matrix mismatch can be considered to constitute a component of precision. In the case of horizontal methods, a comprehensive characterization of method performance should thus include matrix mismatch. The different precision and matrix-mismatch components can be estimated by means of mixed linear models. Results: A relatively simple single-lab design with spiked sample material is presented here, allowing an estimate of matrix mismatch via ANOVA calculations. Conclusions:  In the statistical model for precision experiments described in ISO 5725-2, there is no matrix mismatch term. Indeed, a characterization of matrix mismatch is not possible if only one matrix is represented in the collaborative study, or if the samples sent to the laboratories do not reflect the properties of the matrices of “true” samples. If matrix mismatch was not estimated in the validation study, a subsequent single-lab study can be conducted. A relatively simple design was described, but more sophisticated designs may present various advantages.