Comparative study of robustness of statistical methods for laboratory proficiency testing.

A Monte Carlo approach has been applied to investigate the statistical properties of data analysis methods for proficiency testing, namely, the median-nIQR, Q-method, Algorithm A and Classical method. Simulations were carried out by using a population consisting of two normal distributions, a main population without bias and a sub-population with bias. The difference for robustness among the methods has been discussed. An actual PT for a dioxin isomer was well interpreted by using the population model employed in this study.