Evaluation of analytical performance based on partial order methodology

被引:14
作者
Carlsen, Lars [1 ,2 ]
Bruggernann, Rainer [3 ]
Kenessova, Olga [4 ]
Erzhigitov, Erkin [4 ]
机构
[1] Awareness Ctr, DK-4000 Roskilde, Denmark
[2] Kazakh British Tech Univ, Dept Chem Engn, Alma Ata, Kazakhstan
[3] Leibniz Inst Freshwater Ecol & Inland Fisheries, Dept Ecohydrol, D-12587 Berlin, Germany
[4] RSE Kazakh Inst Metrol, Alma Ata, Kazakhstan
关键词
Analytical performance; Partial order; Posets; Hasse diagram; Multi-indicator systems; AVERAGED RANKS; LATTICE; SETS; TOOL;
D O I
10.1016/j.talanta.2014.09.009
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Classical measurements of performances are typically based on linear scales. However, in analytical chemistry a simple scale may be not sufficient to analyze the analytical performance appropriately. Here partial order methodology can be helpful. Within the context described here, partial order analysis can be seen as an ordinal analysis of data matrices, especially to simplify the relative comparisons of objects due to their data profile (the ordered set of values an object have). Hence, partial order methodology offers a unique possibility to evaluate analytical performance. In the present data as, e.g., provided by the laboratories through interlaboratory comparisons or proficiency testings is used as an illustrative example. However, the presented scheme is likewise applicable for comparison of analytical methods or simply as a tool for optimization of an analytical method. The methodology can be applied without presumptions or pretreatment of the analytical data provided in order to evaluate the analytical performance taking into account all indicators simultaneously and thus elucidating a "distance" from the true value. In the present illustrative example it is assumed that the laboratories analyze a given sample several times and subsequently report the mean value, the standard deviation and the skewness, which simultaneously are used for the evaluation of the analytical performance. The analyses lead to information concerning (1) a partial ordering of the laboratories, subsequently, (2) a "distance" to the Reference laboratory and (3) a classification due to the concept of "peculiar points". (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:285 / 293
页数:9
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