Estimation of measurement uncertainty by using regression techniques and spiked samples

In this paper, we describe how to assess the trueness of analytical procedu res using spiked samples and regression techniques. We show then how to cal culate the uncertainty of future samples using the information generated in this process. Two types of bias are calculated in the assessment of truene ss: a proportional bias (normally expressed in terms of recovery) and a con stant bias. Since in many cases blank samples are not available, we propose a method for assessing trueness when samples that already contain the nati ve analyte are spiked at several levels of concentration. Only proportional bias can be estimated from spiked samples, while constant bias must be est imated by the Youden method, i.e. by taking different amounts of sample. We propose two ways of assessing trueness. The first expresses results as ins trumental responses and the second expresses results as concentration. We t hen present expressions for calculating uncertainty that cover these two si tuations. Finally, we use the expressions to calculate uncertainty from val idation data of the analysis of esters in wine by SPME-GC. (C) 2001 Elsevie r Science B.V. All rights reserved.