Keithley Richard B, Heien Michael L, Wightman R Mark
The University of North Carolina, Department of Chemistry, B-5 Venable Hall CB#3290, Chapel Hill, NC 27599, USA.
Trends Analyt Chem. 2009 Oct 1;28(9):1127-1136. doi: 10.1016/j.trac.2009.07.002.
Data analysis is an essential tenet of analytical chemistry, extending the possible information obtained from the measurement of chemical phenomena. Chemometric methods have grown considerably in recent years, but their wide use is hindered because some still consider them too complicated. The purpose of this review is to describe a multivariate chemometric method, principal component regression, in a simple manner from the point of view of an analytical chemist, to demonstrate the need for proper quality-control (QC) measures in multivariate analysis and to advocate the use of residuals as a proper QC method.
数据分析是分析化学的一项基本原则,它扩展了从化学现象测量中获得的可能信息。近年来,化学计量学方法有了显著发展,但其广泛应用受到阻碍,因为一些人仍然认为它们过于复杂。本综述的目的是以分析化学家的视角,以一种简单的方式描述一种多元化学计量学方法——主成分回归,论证在多元分析中采取适当质量控制(QC)措施的必要性,并提倡将残差用作一种合适的QC方法。