Tutorial and spreadsheet for the evaluation of instrumental quantification uncertainty by the linear weighted regression model: Determination of elemental impurities in a nasal spray by ICP-MS

Abstract

A tutorial and spreadsheet for the validation and bottom-up uncertainty evaluation of quantifications performed by instrumental methods of analysis based on linear weighted calibrations is presented. The developed tool automatically assesses if calibrator values uncertainty is negligible given instrumental signal precision, assesses signal homoscedasticity by the Levene's test, guides the selection of weighting factors and evaluates the fitness of the regression model to define the calibration curve. The spreadsheet allows the use of the linear weighted regression model without the need for collecting many replicate signals of calibrators and sample by taking previously developed detailed models of signal precision variation in the calibration interval after adjustments to the daily precision conditions. This tool was successfully applied to the determination of the mass concentration of Cd, Pb, As, Hg, Co, V and Ni in a nasal spray by ICP-MS after samples dilution and acidification. The developed uncertainty models were checked through the analysis of nasal sprays after spiking with known analyte concentration levels. The metrological compatibility between estimated and reference analyte levels for 95% or 99% confidence level supports uncertainty model adequacy. The spiked samples were quantified from many replicate signals but uncertainty evaluation from duplicate calibrator and sample signals was assessed by randomly selecting calibrators and sample signals and by numerically defining a minimum acceptable success rate of the compatibility tests. The developed model was proven adequate to quantify the uncertainty of the studied measurements.