1932

Abstract

Forensic science refers to the use of scientific methods in a legal context. Several recent events, especially the release in 2009 of the National Research Council (NRC) report , have raised concerns about the methods used to analyze forensic evidence and the ways in which forensic evidence is interpreted and reported on in court. The NRC report identified challenges including the lack of resources in many jurisdictions compared with the amount of evidence requiring processing, the lack of standardization across laboratories and practitioners, and questions about the analysis, interpretation and presentation of evidence. With respect to the last, the NRC report raises questions about the underlying scientific foundation for forensic examinations on some evidence types. Statistics has emerged as a key discipline for helping the forensic science community address these challenges. The standard elements of statistical analysis—study design, data collection, data analysis, statistical inference, and summarizing and reporting inferences—are all relevant. This article reviews the role of forensic evidence, the heterogeneity of forensic domains, current practices and their limitations, and the potential contributions of more rigorous statistical methods, especially Bayesian approaches and the likelihood ratio, in the analysis, interpretation, and reporting of forensic evidence.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-statistics-041715-033554
2017-03-07
2024-03-28
Loading full text...

Full text loading...

/deliver/fulltext/statistics/4/1/annurev-statistics-041715-033554.html?itemId=/content/journals/10.1146/annurev-statistics-041715-033554&mimeType=html&fmt=ahah

Literature Cited

  1. Aitken CGG, Lucy D. 2004. Evaluation of trace evidence in the form of multivariate data. Appl. Stat. 53:109–22 [Google Scholar]
  2. Almirall J, Trejos T. 2006. Advances in the forensic analysis of glass fragments: a review with focus on refractive index and elemental analysis. Forensic Sci. Rev. 18:274–95 [Google Scholar]
  3. Butler JM. 2015. Advanced Topics in Forensic DNA Typing: Interpretation San Diego: Academic Press
  4. Carriquiry AL, Daniels M, Stern HS. 2000. Statistical treatment of class evidence: Trace element concentrations in bullet lead. Technical Report, Iowa State University
  5. Daubert v. Merrell Dow Pharmaceuticals, Inc. 509 U.S. 579 (1993)
  6. Dettman JR, Cassabaum AA, Saunders CP, Snyder DL, Buscaglia J. 2014. Forensic discrimination of copper wire using trace element concentrations. Anal. Chem. 86:8176–82 [Google Scholar]
  7. Dror IE, Charlton D, Peron A. 2006. Contextual information renders experts vulnerable to making erroneous identifications. Forensic Sci. Int. 156:74–78 [Google Scholar]
  8. Dror IE, Thompson WC, Meissner CA, Kornfield I, Krane D. et al. 2015. Content management toolbox: a linear sequential unmasking (LSU) approach for minimizing cognitive bias in forensic decision making. J. Forensic Sci. 60:1111–12 [Google Scholar]
  9. Eckholm E. 2016. Texas panel calls for an end to criminal IDs via bite mark. New York Times Feb. 12 A10
  10. ENFSI (Eur. Netw. Forensic Sci. Inst.) 2015. ENFSI Guideline for Evaluative Reporting in Forensic Science. Wiesbaden, Ger.: ENFSI http://enfsi.eu/wp-content/uploads/2016/09/m1_guideline.pdf
  11. Expert Work. Group Hum. Factors Latent Print Anal 2012. Latent Print Examination and Human Factors: Improving the Practice through a Systems Approach. Gaithersburg, MD: Natl. Inst. Stand. Technol. and Washington, DC: Natl. Inst. Justice http://www.crime-scene-investigator.net/LatentPrintExaminationHumanFactors.pdf
  12. FBI (Fed. Bur. Investig.) 2015. FBI testimony on microscopic hair analysis contained errors in at least 90 percent of cases in ongoing review. Press Release, April 20. https://www.fbi.gov/news/pressrel/press-releases/fbi-testimony-on-microscopic-hair-analysis-contained-errors-in-at-least-90-percent-of-cases-in-ongoing-review
  13. Fenton N, Neil M, Berger D. 2016. Bayes and the law. Annu. Rev. Stat. Appl. 3:51–77 [Google Scholar]
  14. Fienberg SE. 1989. The Evolving Role of Statistical Assessments as Evidence in the Courts New York: Springer
  15. Fine GA. 2006. A Review of the FBI's Handling of the Brandon Mayfield Case (Unclassified and Redacted) Washington, DC: US Dep. Justice Off. Insp. Gen https://oig.justice.gov/special/s0601/final.pdf
  16. Frye v. United States 293 F. 1013 (1923)
  17. Garris MD, McCabe RM. 2000. NIST Special Database 27: fingerprint minutiae from latent and matching tenprint images. Tech. Rep. NISTIR 6534. Natl. Inst. Stand. Technol., Gaithersburg, MD
  18. Hepler AB, Saunders CP, Davis LJ, Buscaglia J. 2012. Score-based likelihood ratios for handwriting evidence. Forensic Sci. Int. 219:129–40 [Google Scholar]
  19. Kelly H, Bright J, Buckleton JS, Curran JM. 2014. A comparison of statistical models for the analysis of complex forensic DNA profiles. Sci. Justice 54:166–70 [Google Scholar]
  20. Lehmann EL, Romano JP. 2008. Testing Statistical Hypotheses New York: Springer, 3rd ed..
  21. Lindley DV. 1977. A problem in forensic science. Biometrika 64:207–13 [Google Scholar]
  22. Martire KA, Kemp RI, Watkins I, Sayle MA, Newell BR. 2013. The expression and interpretation of uncertain forensic science evidence: verbal equivalence, evidence strength, and the weak evidence effect. Law Hum. Behav. 37:197–207 [Google Scholar]
  23. NCFS (Natl. Comm. Forensic Sci.) 2015. Ensuring that forensic analysis is based upon task-relevant information. Views doc., Natl. Inst. Stand. Technol., Gaithersburg, MD
  24. NCFS (Natl. Comm. Forensic Sci.) 2016. Views of the Commission regarding use of the term reasonable scientific certainty Views doc., Natl. Inst. Stand. Technol., Gaithersburg, MD
  25. NRC (Natl. Res. Counc.) 1996. The Evaluation of Forensic DNA Evidence Washington, DC Natl. Acad. Press:
  26. NRC (Natl. Res. Counc.) 2003. The Polygraph and Lie Detection Washington, DC Natl. Acad. Press:
  27. NRC (Natl. Res. Counc.) 2004. Forensic Analysis: Weighing Bullet Lead Evidence Washington, DC Natl. Acad. Press:
  28. NRC (Natl. Res. Counc.) 2008. Ballistic Imaging Washington, DC Natl. Acad. Press:
  29. NRC (Natl. Res. Counc.) 2009. Strengthening Forensic Science in the United States: A Path Forward Washington, DC Natl. Acad. Press:
  30. Neumann C, Champod C, Yoo M, Genessay T, Langenburg G. 2015. Quantifying the weight of fingerprint evidence through the spatial relationship, directions and types of minutiae observed on fingermarks. Forensic Sci. Int. 248:154–71 [Google Scholar]
  31. Neumann C, Evett IW, Skerrett J. 2012. Quantifying the weight of evidence from a forensic fingerprint comparison: a new paradigm. J. R. Stat. Soc. A 175:371–415 [Google Scholar]
  32. Neumann C, Stern H. 2016. Forensic examination of fingerprints: past, present and future. Chance 29:19–16 [Google Scholar]
  33. PCAST (Pres. Counc. Advis. Sci. Technol.) 2016. Report to the President: Forensic Science in Criminal Courts: Ensuring Scientific Validity of Feature-Comparison Methods Washington, DC: Executive Off. Pres http://www.crime-scene-investigator.net/PDF/forensic-science-in-criminal-courts-ensuring-scientific-validity-of-feature-comparison-methods.pdf
  34. Pepe MS. 2003. The Statistical Evaluation of Medical Tests for Classification and Prediction New York: Oxford Univ. Press
  35. Saks MJ, Albright T, Bohan TL, Bierer BE, Bowers CM. et al. 2016. Forensic bitemark identification: weak foundations, exaggerated claims. J. Law Biosci. https://doi.org/10.1093/jlb/lsw045
  36. Steele CD, Balding DJ. 2014. Statistical evaluation of forensic DNA profile evidence. Annu. Rev. Stat. Appl. 1:361–84 [Google Scholar]
  37. Taroni F, Bozza S, Biedermann A, Aitken C. 2016. Dismissal of the illusion of uncertainty in the assessment of a likelihood ratio. Law Prob. Risk 15:11–16 [Google Scholar]
  38. Thompson WC, Newman EJ. 2015. Lay understanding of forensic statistics: evaluation of random match probabilities, likelihood ratios, and verbal equivalents. Law Hum. Behav. 39:332–49 [Google Scholar]
  39. Ulery BT, Hicklin RA, Buscaglia J, Roberts MA. 2011. Accuracy and reliability of forensic latent fingerprint decisions. PNAS 108:7733–38 [Google Scholar]
  40. Ulery BT, Hicklin RA, Buscaglia J, Roberts MA. 2012. Repeatability and reproducibility of decisions by latent fingerprint examiners. PLOS ONE 7:e32800 [Google Scholar]
  41. Zweig MH, Campbell G. 1993. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin. Chem. 39:4561–77 [Google Scholar]
/content/journals/10.1146/annurev-statistics-041715-033554
Loading
/content/journals/10.1146/annurev-statistics-041715-033554
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error