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In this paper, we describe how to assess the trueness of analytical procedures using spiked samples and regression techniques. We show then how to calculate the uncertainty of future samples using the information generated in this process. Two types of bias are calculated in the assessment of trueness: a proportional bias (normally expressed in terms of recovery) and a constant bias. Since in many...
We propose a new procedure for estimating the uncertainty in quantitative routine analysis. This procedure uses the information generated when the trueness of the analytical method is assessed from recovery assays. In this paper, we assess trueness by estimating proportional bias (in terms of recovery) and constant bias separately. The advantage of the procedure is that little extra work needs to...
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