Comparison of different statistical methods for evaluation of proficiency test data

In analytical chemistry, proficiency testing usually consists in tests that laboratories conduct under routine conditions and report the result to the PT provider who then converts the result to a score which helps the participant to assess the accuracy of the result. The aim of this work is to show PT providers, accreditations bodies, and participating laboratories that different scoring results can be achieved depending on the evaluation system selected. The influence of different evaluation techniques on the results of an interlaboratory comparison for determination of gold in precious metals alloys was investigated. Results from 19 participating laboratories were evaluated by means of the three procedures: (1) classical statistical approach—outliers detection; (2) robust methods—(2A) robust procedure and (2B) ISO 13528; and (3) fitness for purpose. Evaluation of the same PT data revealed very interesting issues depending on the different scoring systems that were used and the robustness of the statistical methods used for detecting outliers. As a general rule, laboratories with scoring Z > 2 offered clearly poorer performance in robust approaches than classical ones. In order to support this first evidence, we evaluated a second data set with results from 24 laboratories (mercury from soil samples) by means of the four mentioned approaches. Selection and comparison of different scoring systems must be done very carefully, because sometimes they are not the best approach for studying the data population or the more appropriate one for evaluating the distribution of the data. Finally it should be taken into account that sometimes the robust scoring systems are not always suitable for evaluating the results of some PT schemes.