Literature DB >> 21639327

Weighted least-squares approach to calculating limits of detection and quantification by modeling variability as a function of concentration.

M E Zorn1, R D Gibbons, W C Sonzogni.   

Abstract

The limit of detection and limit of quantification are current critical issues in environmental testing. In most laboratories, limits are currently calculated on the basis of the standard deviation of replicate analyses at a single concentration. However, since the standard deviation depends on concentration, these single-concentration techniques result in limits that are directly dependent on spiking concentration. A more rigorous approach uses a weighted least-squares regression analysis of replicates spiked at a series of concentrations [Formula: see text] a calibration design. In this work, the use of weighted tolerance intervals is introduced for estimating detection and quantification limits. In addition, models for estimating the weights used in calculating weighted prediction intervals and weighted tolerance intervals are presented. Using this method, detection and quantification limits were calculated for gas chromatographic analyses of 16 polychlorinated biphenyls. Results show that the approach developed provides improved estimates of analytical limits and that the single-concentration approaches currently in wide use are seriously flawed. Future work should reduce the data needed for the calibration design approach so that more rigorous detection and quantification limits can be routinely applied.

Entities:  

Year:  1997        PMID: 21639327     DOI: 10.1021/ac970082i

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  6 in total

1.  Interlaboratory evaluation of automated, multiplexed peptide immunoaffinity enrichment coupled to multiple reaction monitoring mass spectrometry for quantifying proteins in plasma.

Authors:  Eric Kuhn; Jeffrey R Whiteaker; D R Mani; Angela M Jackson; Lei Zhao; Matthew E Pope; Derek Smith; Keith D Rivera; N Leigh Anderson; Steven J Skates; Terry W Pearson; Amanda G Paulovich; Steven A Carr
Journal:  Mol Cell Proteomics       Date:  2011-12-22       Impact factor: 5.911

2.  Nonlinear Regression Improves Accuracy of Characterization of Multiplexed Mass Spectrometric Assays.

Authors:  Cyril Galitzine; Jarrett D Egertson; Susan Abbatiello; Clark M Henderson; Lindsay K Pino; Michael MacCoss; Andrew N Hoofnagle; Olga Vitek
Journal:  Mol Cell Proteomics       Date:  2018-02-09       Impact factor: 5.911

3.  EPR dosimetry intercomparison using smart phone touch screen glass.

Authors:  Paola Fattibene; Francois Trompier; Albrecht Wieser; Maria Brai; Bartlomej Ciesielski; Cinzia De Angelis; Sara Della Monaca; Tristan Garcia; H Gustafsson; Eli Olag Hole; M Juniewicz; K Krefft; Anna Longo; Philippe Leveque; Eva Lund; Maurizio Marrale; Barbara Michalec; Gabriela Mierzwińska; J L Rao; Alexander A Romanyukha; Hasan Tuner
Journal:  Radiat Environ Biophys       Date:  2014-03-27       Impact factor: 1.925

4.  Laboratory estimation of net trophic transfer efficiencies of PCB Congeners to lake trout (Salvelinus namaycush) from its prey.

Authors:  Charles P Madenjian; Richard R Rediske; James P O'Keefe; Solomon R David
Journal:  J Vis Exp       Date:  2014-08-29       Impact factor: 1.355

5.  A single-source photon source model of a linear accelerator for Monte Carlo dose calculation.

Authors:  Obioma Nwankwo; Gerhard Glatting; Frederik Wenz; Jens Fleckenstein
Journal:  PLoS One       Date:  2017-09-08       Impact factor: 3.240

6.  Assessing the detection capacity of microarrays as bio/nanosensing platforms.

Authors:  Ju Seok Lee; Joon Jin Song; Russell Deaton; Jin-Woo Kim
Journal:  Biomed Res Int       Date:  2013-11-13       Impact factor: 3.411

  6 in total

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