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Statistical methods for evaluating the linearity in assay validation
Author(s) -
Hsieh Eric,
Hsiao Chinfu,
Liu Jenpei
Publication year - 2009
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1194
Subject(s) - linearity , metric (unit) , mathematics , statistics , power (physics) , computer science , physics , operations management , quantum mechanics , economics
One of the most important characteristics for evaluation of the accuracy in assay validation is the linearity. Kroll, et al . 1 proposed a method based on the average deviation from linearity (ADL) to evaluate the linearity. Hsieh and Liu 2 suggested that hypothesis for proving the linearity be formulated as the alternative hypothesis and proposed the corrected Kroll's method. However, the issue concerning the variability in estimation of the non‐centrality parameter is still unresolved. Consequently, the type I error rates may still be inflated for the corrected Kroll's method. To overcome this issue, we propose the sum of squares of deviations from linearity (SSDL) as an alternative metric for evaluation of linearity. Based on SSDL, we applied the method of generalized pivotal quantities (GPQ) for the inference of evaluation of linearity. The simulation studies were conducted to empirically investigate the size and power between current and proposed methods. The simulation results show that the proposed GPQ method not only adequately control size but also provide sufficient power than other methods. A numeric example illustrates the proposed methods. Copyright © 2008 John Wiley & Sons, Ltd.