Abstract
In this study we demonstrate that the method of standard additions can provide unreliable results in chemical analysis when the linear calibration model is forced to fit the data. A well designed standard addition experiment can still yield results biased by 10% when the analyst relies only on the linear model. Recently, the Joint Committee for Guides in Metrology (GUM-6) has emphasized the need to address the uncertainty inherent to the choice of measurement models and here we show how model averaging can provide a practical way to account for model uncertainty in the method of standard additions.
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