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

Pluháček, Tomáš; Milde, David; Součková, Jitka; Silva, Ricardo J.N. Bettencourt da

doi:10.1016/j.talanta.2020.122044

Cited by 8 publications

(4 citation statements)

References 28 publications

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“…This is in line with reports in literature about ICP-MS data being heteroscedastic in most cases. 9,14,30 It has been discussed as a partially intrinsic problem of count based data, whose distribution can be reasonably described by a Poisson distribution. 14,27 This directly implies a functional dependency of the standard deviation on the average count and therefore rules out a constant variance throughout the entire concentration range.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

“…Another requirement for simple linear regression is that the uncertainty of the calibrator concentration does not affect the regression result. 9,31 As the concentrations of matrix-matched gelatin standards are often validated by externally calibrated ICP-MS analysis after acidic digestion, this is an important aspect to check prior to the application of simple linear regression. In this study, the relative uncertainty in the calibrator concentration, determined by ICP-MS analysis, was found to be smaller by a factor of around 10 than the standard deviation of the LA-ICP-MS signal of the respective gelatin standard and therefore considered negligible.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

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Weighted Linear Regression Improves Accuracy of Quantitative Elemental Bioimaging by Means of LA-ICP-MS

2021

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The application of ordinary least squares (OLS) linear regression is widely used in order to approximate linear external calibration data. However, the assumption of homoscedasticity is often not considered as a requirement for correct data approximation, which can result in a poor regression fit that is often more prominent in the lower concentration range. Heteroscedasticity in inductively coupled plasma–mass spectrometry (ICP-MS) data has been discussed in literature as an intrinsic problem and was found to be addressed better by the use of weighted least squares (WLS) regression in multiple studies. In this study, the effects of OLS and WLS linear regression models have been investigated for quantitative imaging experiments by means of laser ablation (LA)–ICP-MS using matrix-matched standards. The calibration data produced by this technique was found to be heteroscedastic in all 60 analyzed datasets, which yielded poor regression fits for OLS linear regression. In comparison to conventional ICP-MS analysis, the resulting negative effects were found to become even more visible in imaging LA-ICP-MS due to an inaccurate estimation of the regression line’s intercept. Also, the calculation of average concentrations in selected regions of interest (ROIs) yields incorrect quantification results at the lower end of the calibration range. The application of WLS linear regression resulted in an improved goodness of fit (GOF), although the weighting factor should be selected carefully. Besides the reciprocal of the variance of each calibration standard (1/si 2 ) , more empirical weighting factors that have been discussed in the literature were also evaluated regarding the GOF.

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Section: ■ Results and Discussionmentioning

confidence: 99%

Section: ■ Results and Discussionmentioning

confidence: 99%

Weighted Linear Regression Improves Accuracy of Quantitative Elemental Bioimaging by Means of LA-ICP-MS

2021

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“…A paper entitled “ Tutorial and spreadsheet for the evaluation of instrumental quantification uncertainty by the linear weighted regression model : determination of elemental impurities in nasal spray by ICP-MS” was presented by Pluhacek et al 76 There is nothing terribly novel about the chemistry in this paper, with samples simply being diluted and acidified prior to analysis. Method validation was through spike/recovery experiments for the analytes As, Cd, Co, Hg, Ni, Pb and V. Despite the lack of novelty in the actual analysis stage, the tutorial is a worthwhile contribution because it is a good example of how to determine uncertainty and is therefore useful from the metrics perspective.…”

Section: Organic Chemical and Materialsmentioning

confidence: 99%

Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials

Carter¹,

Clough

Fisher

et al. 2022

J. Anal. At. Spectrom.

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“…The OLS assumes the linear variation of potential with the reference pH, potential homoscedasticity, and negligible uncertainty of the reference pH values given signal precision [25]. These assumptions should be tested by using adequate tools [26,27].…”

Section: Single Differential Potentiometrymentioning

confidence: 99%

Evaluation and validation of detailed and simplified models of the uncertainty of unified pHabsH2O measurements in aqueous solutions

Silva

Saame

Anes

et al. 2021

Analytica Chimica Acta

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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

Cited by 8 publications

References 28 publications

Weighted Linear Regression Improves Accuracy of Quantitative Elemental Bioimaging by Means of LA-ICP-MS

Weighted Linear Regression Improves Accuracy of Quantitative Elemental Bioimaging by Means of LA-ICP-MS

Atomic spectrometry update: review of advances in the analysis of metals, chemicals and materials

Evaluation and validation of detailed and simplified models of the uncertainty of unified pHabsH2O measurements in aqueous solutions

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