Skip to main content
SpringerLink
Log in

Methodological Approaches to Calculating Key Validation Parameters of Forensic Methods

  • SUBSTANCES ANALYSIS
  • Published:
Inorganic Materials Aims and scope

Abstract

Validation of forensic methods (FMs) is one of the main procedures of standardization of forensic activities aimed at verifying the reliability of the results. This procedure is extensively used in organizations of the European Network of Forensic Science Institutes (ENFSI), which includes the Russian Federal Centre of Forensic Science of the Ministry of Justice of the Russian Federation (RFCFS). In terms of metrology, FMs can be divided into two types: forensic measurement methods (FMMs) and forensic testing methods (FTMs). In an earlier paper, the authors have shown that methodological approaches to FMM validation are well developed and are actively used in RFCFS laboratories, but FTM validation procedures are still a very questionable matter of extensive discussion in scientific literature. The most significant difficulties in FT validation are related to selecting validation parameters, developing the validation experiment, and performing statistical calculations. This article proposes methodological approaches to statistical assessment of FMM and FTM parameters that can be used in forensic practice. A number of recommendations for the validation procedure, a list of validation parameters, and some designs of specific experiments of FMM and FTM quality assessment are also provided. Fitness of FMMs is assessed by repeatedly measuring a monitored indicator in reference samples and standard additions using standard formulas for calculating statistical parameters. The FTM validation procedure is considered by the example of the FTM “Microscopic Examination of Textile Fibers” in which the test samples were fibers from the laboratory collection with known tested characteristics. It is demonstrated that, when assessing the reliability of FTMs and the competence of experts, it is efficient to use probabilistic estimates of the rate of false test results and to calculate the likelihood ratio.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.

Similar content being viewed by others

REFERENCES

  1. Smirnova, S.A., Omel’yanyuk, G.G., and Bebeshko, G.I., Methodological approaches to the validation of forensic methods, including measurement methods (MM), Teor. Prakt. Sud. Ekspert., 2012, no. 1 (25), pp. 50–62.

  2. GOST (State Standard) R ISO 5725-2002: Accuracy (Trueness and Precision) of Measurement Methods and Results, Moscow: Izd. Standartov, 2002, parts 1–6.

  3. RMG-61-2010. Pokazateli tochnosti, pravil’nosti, pretsizionnosti metodiki kolichestvennogo khimicheskogo analiza. Metod otsenki (RMG-61-2010: Accuracy, Correctness, and Precision of the Quantitative Chemical Analysis Procedures, Evaluation Methods), Moscow: Standartinform, 2013.

  4. Quantifying Uncertainty in Analytical Measurement: EURACHEM-CITAC Guide, Ellison, S.L.R., Rosslein, M., and Williams, A., Eds., Teddington: EuraChem, 2000, no. QUAM:2012.P1.

  5. Smirnova, S.A., Omel’yanyuk, G.G., Usov, A.I., and Bebeshko, G.I., Special considerations in applying the key terms and definitions of the international standard GOST ISO/IEC 17025–2009 in forensic science laboratories, Teor. Prakt. Sud. Ekspert., 2012, no. 2 (26), pp. 57–67.

  6. Paneva, V.I., Assessment of the suitability of quantitative analysis methods in the laboratory, Zavod. Lab., Diagn. Mater., 2008, vol. 74, no. 8, pp. 68–72.

    Google Scholar 

  7. Prichard, E. and Barwik, V., Quality Assurance in Analytical Chemistry, Chichester: Wiley, 2007.

    Book  Google Scholar 

  8. Mezhdunarodnyi slovar’ po metrologii (International Vocabulary of Metrology), St. Petersburg: Professional, 2010.

  9. ISO/IEC GUIDE 99:2007: International Vocabulary of Metrology—Basic and General Concepts and Associated Terms (VIM), Geneva: Int. Stand. Org., 2007. http://www.iso.org/standard/45324.html.

  10. Bebeshko, G.I., Omel’yanyuk, G.G., Nikulina, M.V., and Valitova, A.R., A practice of validation of method of determination of pH and specific electrical conductivity in the objects of soil-geological origin for production of forensic environmental examination in the absence of standard samples, Teor. Prakt. Sud. Ekspert., 2017, vol. 12, no. 2, pp. 66–74.

    Article  Google Scholar 

  11. Smirnova, S.A., Omel’yanyuk, G.G., Bebeshko, G.I., and Yudin, N.V., The experience of validation of measurement method “The determination of benzo(a)pyrene concentration in the objects of soil-geological origin by means of HPLC fluorimetry detecting method” for production of forensic environmental examination, Teor. Prakt. Sud. Ekspert., 2012, no. 3 (27), pp. 79–91.

  12. MUK 4.1.1274-03. Metody kontrolya. Khimicheskie faktory. Izmerenie massovoi doli benz(a)pirena v probakh pochv, gruntov, donnykh otlozhenii i tverdykh otkhodov metodom VEZhKh s ispol’zovaniem fluorimetricheskogo detektora (MUK 4.1.1274-03. Test Methods. Chemical Factors. Measurement of the Mass Fraction of Benz(a)pyrene in Soil, Sediments, and Solid Waste Samples by HPLC using a Fluorometric Detector), Moscow: Minist. Zdravookhr. Ross., 2003.

  13. Doerffel, K., Analytical science—a discipline between chemistry and metrology, Fresenius J. Anal. Chem., 1998, vol. 363, no. 5, pp. 393–394.

    Article  Google Scholar 

  14. Doerffel, K., Statistik in Der Analytischen Chemie, Leipzig: Dtsch. Verlag Grundstoffind., 1966.

    Google Scholar 

  15. Gauthier, T.D., Statistical methods, in Introduction to Environmental Forensics, Murphy, B.L. and Morrison, R.D., Eds., London: Elsevier, 2004, ch. 10, pp. 391–428.

    Google Scholar 

  16. The Expression of Uncertainty in Qualitative Testing: EUACHEM/CITAC Guide, Teddington: EuraChem, 2003, no. LGCN/ VAM/2003/048/.

  17. Pulido, A., Ruisánchez, I., Boqueì, R., and Rius, F.X., Uncertainty of results in routine qualitative analysis, TrAC, Trends Anal. Chem., 2003, vol. 22, no. 10, pp. 647–654. https://doi.org/10.1016/S0165-9936(03)01104-X

    Article  CAS  Google Scholar 

  18. Ellison, S.L.R. and Fearn, T., Characterizing the performance of qualitative analytical methods: Statistics and terminology, TrAC, Trends Anal. Chem., 2005, vol. 24, no. 6, pp. 468–476. https://doi.org/10.1016/j.trac.2005.03.007

    Article  CAS  Google Scholar 

  19. Trullols, E., Ruisaìnchez, I., Rius, F.X., and Huguet, J., Validation of qualitative methods of analysis that use control samples, TrAC, Trends Anal. Chem., 2004, vol. 23, no. 2, pp. 137–145. https://doi.org/10.1016/j.trac.2005.04.001

    Article  CAS  Google Scholar 

  20. Panteleimonov, A.V., Nikitina, N.A., Reshetnyak, E.A., et al., Binary response procedures of qualitative analysis: methodological characteristics and calculation aspects, Metody Ob’ekty Khim. Anal., 2008, vol. 3, no. 2, pp. 128–146.

    Google Scholar 

  21. Mil’man, B.L., Introduction to forensic identification. – St. Petersburg: VVM, 2008.

    Google Scholar 

  22. Mil’man, B.L. and Konopel’ko, L.A., Uncertainty of qualitative chemical analysis: General methodology and binary test methods, J. Anal. Chem., 2004, vol. 59, no. 12, pp. 1128–1141. https://doi.org/10.1023/B:SANC.0000049712.88066.e7

    Article  Google Scholar 

  23. Mil’man, B.L., Identification of chemical compounds, TrAC, Trends Anal. Chem., 2005, vol. 24, no. 6, pp. 493–508. https://doi.org/10.1016/j.trac.2005.03.013.https://doi.org/10.1016/j.trac.2005.03.013

  24. Smirnova, S.A., Bebeshko, G.I., Lyubetskaya, I.P., et al., Probability-based validation of the forensic method “Microscopic analysis of textile fibers,” Teor. Prakt. Sud. Ekspert., 2019, vol. 14, no. 2, pp. 92–99. https://doi.org/10.30764/1819-2785-2019-14-2-92-99

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Russian Federal Center of Forensic Science of the Ministry of Justice (RFCFS), 109028, Moscow, Russia

    G. I. Bebeshko, I. P. Lyubetskaya, G. G. Omel’yanyuk & A. I. Usov

  2. Peoples’ Friendship University of Russia (RUDN), 117198, Moscow, Russia

    G. G. Omel’yanyuk & A. I. Usov

  3. Bauman Moscow State Technical University, 105005, Moscow, Russia

    G. G. Omel’yanyuk & A. I. Usov

Authors
  1. G. I. Bebeshko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. I. P. Lyubetskaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. G. G. Omel’yanyuk
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. I. Usov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to G. I. Bebeshko.

Additional information

Translated by A. Ovchinnikova

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bebeshko, G.I., Lyubetskaya, I.P., Omel’yanyuk, G.G. et al. Methodological Approaches to Calculating Key Validation Parameters of Forensic Methods. Inorg Mater 57, 1385–1392 (2021). https://doi.org/10.1134/S0020168521140028

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0020168521140028

Keywords:

Search

Navigation