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Taylor D, Kokshoorn B, Champod C. A practical treatment of sensitivity analyses in activity level evaluations. Forensic Sci Int 2024; 355:111944. [PMID: 38277913 DOI: 10.1016/j.forsciint.2024.111944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 01/09/2024] [Accepted: 01/15/2024] [Indexed: 01/28/2024]
Abstract
Evaluations of forensic observations considering activity level propositions are becoming more common place in forensic institutions. A measure that can be taken to interrogate the evaluation for robustness is called sensitivity analysis. A sensitivity analysis explores the sensitivity of the evaluation to the data used when assigning probabilities, or to the level of uncertainty surrounding a probability assignment, or to the choice of various assumptions within the model. There have been a number of publications that describe sensitivity analysis in technical terms, and demonstrate their use, but limited literature on how that theory can be applied in practice. In this work we provide some simplified examples of how sensitivity analyses can be carried out, when they are likely to show that the evaluation is sensitive to underlying data, knowledge or assumptions, how to interpret the results of sensitivity analysis, and how the outcome can be reported. We also provide access to an application to conduct sensitivity analysis.
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Affiliation(s)
- Duncan Taylor
- Forensic Science SA, GPO Box 2790, Adelaide, SA 5001, Australia; School of Biological Sciences, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia.
| | - Bas Kokshoorn
- Netherlands Forensic Institute, P.O.Box 24044, 2490 AA The Hague, the Netherlands; Forensic Trace Dynamics, Faculty of Technology, Amsterdam University of Applied Sciences, Amsterdam, the Netherlands
| | - Christophe Champod
- Faculty of Law, Criminal Justice and Public Administration, School of Criminal Justice, University of Lausanne, Lausanne-Dorigny, Switzerland
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2
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Williams JP, Ommen DM, Hannig J. Generalized fiducial factor: An alternative to the Bayes factor for forensic identification of source problems. Ann Appl Stat 2023. [DOI: 10.1214/22-aoas1632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
| | | | - Jan Hannig
- Department of Statistics and Operations Research, UNC at Chapel Hill and National Institute of Standards and Technology
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3
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Gill P, Benschop C, Buckleton J, Bleka Ø, Taylor D. A Review of Probabilistic Genotyping Systems: EuroForMix, DNAStatistX and STRmix™. Genes (Basel) 2021; 12:1559. [PMID: 34680954 PMCID: PMC8535381 DOI: 10.3390/genes12101559] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/24/2021] [Accepted: 09/28/2021] [Indexed: 11/24/2022] Open
Abstract
Probabilistic genotyping has become widespread. EuroForMix and DNAStatistX are both based upon maximum likelihood estimation using a γ model, whereas STRmix™ is a Bayesian approach that specifies prior distributions on the unknown model parameters. A general overview is provided of the historical development of probabilistic genotyping. Some general principles of interpretation are described, including: the application to investigative vs. evaluative reporting; detection of contamination events; inter and intra laboratory studies; numbers of contributors; proposition setting and validation of software and its performance. This is followed by details of the evolution, utility, practice and adoption of the software discussed.
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Affiliation(s)
- Peter Gill
- Forensic Genetics Research Group, Department of Forensic Sciences, Oslo University Hospital, 0372 Oslo, Norway;
- Department of Forensic Medicine, Institute of Clinical Medicine, University of Oslo, 0315 Oslo, Norway
| | - Corina Benschop
- Division of Biological Traces, Netherlands Forensic Institute, P.O. Box 24044, 2490 AA The Hague, The Netherlands;
| | - John Buckleton
- Department of Statistics, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand;
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand
| | - Øyvind Bleka
- Forensic Genetics Research Group, Department of Forensic Sciences, Oslo University Hospital, 0372 Oslo, Norway;
| | - Duncan Taylor
- Forensic Science SA, GPO Box 2790, Adelaide, SA 5001, Australia;
- School of Biological Sciences, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia
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4
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Ommen DM, Saunders CP. A Problem in Forensic Science Highlighting the Differences between the Bayes Factor and Likelihood Ratio. Stat Sci 2021. [DOI: 10.1214/20-sts805] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- Danica M. Ommen
- Danica M. Ommen is Assistant Professor, Department of Statistics, Iowa State University, Ames, Iowa 50011, USA
| | - Christopher P. Saunders
- Christopher P. Saunders is Associate Professor, Department of Mathematics & Statistics, South Dakota State University, Brookings, South Dakota 57007, USA
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5
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Linden J, Taroni F, Marquis R, Bozza S. Bayesian multivariate models for case assessment in dynamic signature cases. Forensic Sci Int 2020; 318:110611. [PMID: 33290986 DOI: 10.1016/j.forsciint.2020.110611] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 11/02/2020] [Accepted: 11/20/2020] [Indexed: 10/22/2022]
Abstract
Dynamic signatures are recordings of signatures made on digitizing devices such as tablet PCs. These handwritten signatures contain both dynamic and spatial information on every data point collected during the signature movement and can therefore be described in the form of multivariate data. The management of dynamic signatures represents a challenge for the forensic science community through its novelty and the volume of data available. Much as for static signatures, the authenticity of dynamic signatures may be doubted, which leads to a forensic examination of the unknown source signature. The Bayes' factor, as measure of evidential support, can be assigned with statistical models to discriminate between competing propositions. In this respect, the limitations of existing probabilistic solutions to deal with dynamic signature evidence is pointed out and explained in detail. In particular, the necessity to remove the independence assumption between questioned and reference material is emphasized.
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Affiliation(s)
- Jacques Linden
- School of Criminal Justice, University of Lausanne, CH-1015 Lausanne Dorigny, Switzerland.
| | - Franco Taroni
- School of Criminal Justice, University of Lausanne, CH-1015 Lausanne Dorigny, Switzerland
| | - Raymond Marquis
- School of Criminal Justice, University of Lausanne, CH-1015 Lausanne Dorigny, Switzerland
| | - Silvia Bozza
- Dipartimento di Economia, Università Ca' Foscari Venezia, Dorsoduro, 3246, 30123 Venezia VE, Italy; School of Criminal Justice, University of Lausanne, CH-1015 Lausanne Dorigny, Switzerland
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6
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Buckleton JS, Pugh SN, Bright JA, Taylor DA, Curran JM, Kruijver M, Gill P, Budowle B, Cheng K. Are low LRs reliable? Forensic Sci Int Genet 2020; 49:102350. [DOI: 10.1016/j.fsigen.2020.102350] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 06/09/2020] [Accepted: 06/26/2020] [Indexed: 12/20/2022]
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7
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Probabilistic reporting in criminal cases in the United States: A baseline study. Sci Justice 2020; 60:406-414. [DOI: 10.1016/j.scijus.2020.06.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 06/02/2020] [Accepted: 06/07/2020] [Indexed: 11/22/2022]
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8
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Taylor D, Balding D. How can courts take into account the uncertainty in a likelihood ratio? Forensic Sci Int Genet 2020; 48:102361. [PMID: 32769057 DOI: 10.1016/j.fsigen.2020.102361] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 05/17/2020] [Accepted: 07/22/2020] [Indexed: 11/19/2022]
Abstract
As legal practitioners and courts become more aware of scientific methods and evidence evaluation, they are demanding measures of the reliability of expert opinion. In particular, there are calls for error rates to accompany opinion evidence in comparative forensic sciences. While error rates or confidence intervals can be useful for those disciplines that claim to identify the source of a trace, the call for these statistical tools has extended to sciences that present opinions in the form of a likelihood ratio. In this article we argue against presenting both a likelihood ratio and numerical measures of its uncertainty. We explain how the LR already encapsulates uncertainty. Instead we consider how sensitivity analyses can be used to guide the presentation of LRs that are informative to the court and not unfair to defendants.
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Affiliation(s)
- Duncan Taylor
- School of Biological Sciences, Flinders University, GPO Box 2100 Adelaide, SA, 5001, Australia; Forensic Science SA, PO Box 2790, Adelaide, SA, 5000, Australia.
| | - David Balding
- Melbourne Integrative Genomics, School of BioSciences and School of Mathematics & Statistics, University of Melbourne, Australia
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9
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Almirall J, Trejos T, Lambert K. Interpol review of glass and paint evidence 2016-2019. Forensic Sci Int Synerg 2020; 2:404-415. [PMID: 33385139 PMCID: PMC7770445 DOI: 10.1016/j.fsisyn.2020.01.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 01/16/2020] [Indexed: 11/18/2022]
Abstract
This review paper covers the forensic-relevant literature in paint and glass evidence from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.
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Affiliation(s)
- Jose Almirall
- Department of Chemistry and Biochemistry and Center for Advanced Research in Forensic Science, Florida International University, 11200 SW 8th Street, AHC4- 316, Miami, FL, 33199, USA
| | - Tatiana Trejos
- Department of Forensic and Investigative Science, West Virginia University, 208 Oglebay Hall, Morgantown, WV, 26506-6121, USA
| | - Katelyn Lambert
- Department of Chemistry and Biochemistry and Center for Advanced Research in Forensic Science, Florida International University, 11200 SW 8th Street, AHC4- 316, Miami, FL, 33199, USA
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10
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Meilia PDI, Freeman MD, Zeegers MP. A review of causal inference in forensic medicine. Forensic Sci Med Pathol 2020; 16:313-320. [PMID: 32157581 PMCID: PMC7245596 DOI: 10.1007/s12024-020-00220-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2020] [Indexed: 12/01/2022]
Abstract
The primary aim of forensic medical analysis is to provide legal factfinders with evidence regarding the causal relationship between an alleged action and a harmful outcome. Despite existing guides and manuals, the approach to formulating opinions on medicolegal causal inference used by forensic medical practitioners, and how the strength of the opinion is quantified, is mostly lacking in an evidence-based or systematically reproducible framework. In the present review, we discuss the literature describing existing methods of causal inference in forensic medicine, especially in relation to the formulation of expert opinions in legal proceedings, and their strengths and limitations. Causal inference in forensic medicine is unique and different from the process of establishing a diagnosis in clinical medicine. Because of a lack of tangibility inherent in causal analysis, even the term “cause” can have inconsistent meaning when used by different practitioners examining the same evidence. Currently, there exists no universally applied systematic methodology for formulating and assessing causality in forensic medical expert opinions. Existing approaches to causation in forensic medicine generally fall into two categories: intuitive and probabilistic. The propriety of each approach depends on the individual facts of an investigated injury, disease, or death. We opine that in most forensic medical settings, probabilistic causation is the most suitable for use and readily applicable. Forensic medical practitioners need, however, be aware of the appropriate approach to causation for different types of cases with varying degrees of complexity.
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Affiliation(s)
- Putri Dianita Ika Meilia
- Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands.
| | - Michael D Freeman
- Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands
| | - Maurice P Zeegers
- Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+, Universiteitssingel 40, 6229 ER, Maastricht, the Netherlands
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11
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Buckleton JS, Bright JA, Ciecko A, Kruijver M, Mallinder B, Magee A, Malsom S, Moretti T, Weitz S, Bille T, Noël S, Oefelein RH, Peck B, Kalafut T, Taylor DA. Response to: Commentary on: Bright et al. (2018) Internal validation of STRmix™ - A multi laboratory response to PCAST, Forensic Science International: Genetics, 34: 11-24. Forensic Sci Int Genet 2019; 44:102198. [PMID: 31710898 DOI: 10.1016/j.fsigen.2019.102198] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 09/28/2019] [Accepted: 10/30/2019] [Indexed: 10/25/2022]
Affiliation(s)
- John S Buckleton
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142, New Zealand; University of Auckland, Department of Statistics, Auckland, New Zealand
| | - Jo-Anne Bright
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142, New Zealand.
| | - Anne Ciecko
- Midwest Regional Forensic Laboratory, Andover, Minnesota, United States
| | - Maarten Kruijver
- Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142, New Zealand
| | | | | | - Simon Malsom
- Key Forensic Services Ltd., UK, Norwich Laboratory, United Kingdom
| | | | - Steven Weitz
- US Bureau of Alcohol, Tobacco, Firearms, Explosives Laboratory (ATF), United States
| | - Todd Bille
- US Bureau of Alcohol, Tobacco, Firearms, Explosives Laboratory (ATF), United States
| | - Sarah Noël
- Laboratoire de Sciences Judiciaires et de Médecine Légale, Direction Biologie/ADN, 1701 Parthenais, Montréal, Québec, H2K 3S7, Canada
| | | | - Brian Peck
- Center of Forensic Science Toronto, Canada
| | | | - Duncan A Taylor
- Forensic Science South Australia, Australia; University of Adelaide, South Australia, Australia
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12
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Meester R. The Limits of Bayesian Thinking in Court. Top Cogn Sci 2019; 12:1205-1212. [PMID: 31670466 PMCID: PMC7687214 DOI: 10.1111/tops.12478] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 09/16/2019] [Indexed: 11/27/2022]
Abstract
We comment on the contributions of Dahlman and of Fenton et al., who both suggested a Bayesian approach to analyze the Simonshaven case. We argue that analyzing a full case with a Bayesian approach is not feasible, and that there are serious problems with assigning actual numbers to probabilities and priors. We also discuss the nature of Bayesian thinking in court, and the nature and interpretation of the likelihood ratio. In particular, we discuss what it could mean that a likelihood ratio is in some sense uncertain.
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13
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Eldridge H. Juror comprehension of forensic expert testimony: A literature review and gap analysis. Forensic Sci Int Synerg 2019; 1:24-34. [PMID: 32411951 PMCID: PMC7219164 DOI: 10.1016/j.fsisyn.2019.03.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 03/01/2019] [Accepted: 03/04/2019] [Indexed: 11/16/2022]
Abstract
Forensic scientists and commentators including academics and statisticians have been embroiled in a debate over the best way to present evidence in the courtroom. Various forms of evidence presentation, both quantitative and qualitative, have been championed, yet amidst the furor over the most "correct" or "accurate" way to present evidence, the perspective of the fact-finder is often lost. Without comprehension, correctness is moot. Unbeknownst to many forensic practitioners, there is a large, though incomplete, body of literature from the cognitive psychology domain that explores the question of what jurors understand when forensic scientists testify. This body of work has begun to test different proposed methods of testimony in an effort to understand which are most effective at communicating the strength of evidence that is intended by the expert. This article is a review of that literature that is intended for the forensic scientist community. Its aim is to educate that community on the findings of completed studies and to identify suggestions for further research that will inform changes in testimony delivery and ensure that any modifications can be implemented with confidence in their effectiveness.
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Affiliation(s)
- Heidi Eldridge
- RTI International, 3040 E. Cornwallis Rd., Research Triangle Park, NC, 27709, USA
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14
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Konigsberg LW, Frankenberg SR, Liversidge HM. Status of Mandibular Third Molar Development as Evidence in Legal Age Threshold Cases. J Forensic Sci 2018; 64:680-697. [DOI: 10.1111/1556-4029.13926] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 08/31/2018] [Accepted: 09/19/2018] [Indexed: 11/29/2022]
Affiliation(s)
- Lyle W. Konigsberg
- Department of Anthropology University of Illinois at Urbana‐Champaign Urbana IL 61801
| | - Susan R. Frankenberg
- Department of Anthropology University of Illinois at Urbana‐Champaign Urbana IL 61801
| | - Helen M. Liversidge
- Institute of Dentistry, Barts and the London School of Medicine and Dentistry Queen Mary University of London London E1 2AD U.K
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15
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Dynamic signatures: A review of dynamic feature variation and forensic methodology. Forensic Sci Int 2018; 291:216-229. [DOI: 10.1016/j.forsciint.2018.08.021] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Accepted: 08/20/2018] [Indexed: 11/19/2022]
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16
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Evaluation of forensic genetics findings given activity level propositions: A review. Forensic Sci Int Genet 2018; 36:34-49. [DOI: 10.1016/j.fsigen.2018.06.001] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Revised: 05/31/2018] [Accepted: 06/01/2018] [Indexed: 12/31/2022]
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17
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Gittelson S, Berger CEH, Jackson G, Evett IW, Champod C, Robertson B, Curran JM, Taylor D, Weir BS, Coble MD, Buckleton JS. A response to "Likelihood ratio as weight of evidence: A closer look" by Lund and Iyer. Forensic Sci Int 2018; 288:e15-e19. [PMID: 29857959 PMCID: PMC7306225 DOI: 10.1016/j.forsciint.2018.05.025] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 05/15/2018] [Indexed: 11/24/2022]
Abstract
Recently, Lund and Iyer (L&I) raised an argument regarding the use of likelihood ratios in court. In our view, their argument is based on a lack of understanding of the paradigm. L&I argue that the decision maker should not accept the expert's likelihood ratio without further consideration. This is agreed by all parties. In normal practice, there is often considerable and proper exploration in court of the basis for any probabilistic statement. We conclude that L&I argue against a practice that does not exist and which no one advocates. Further we conclude that the most informative summary of evidential weight is the likelihood ratio. We state that this is the summary that should be presented to a court in every scientific assessment of evidential weight with supporting information about how it was constructed and on what it was based.
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Affiliation(s)
- Simone Gittelson
- Centre for Forensic Science, University of Technology Sydney, P.O. Box 123, Broadway, NSW 2007, Australia.
| | - Charles E H Berger
- Leiden University, Institute for Criminal Law and Criminology, P.O. Box 9520, 2300 RA Leiden, The Netherlands
| | - Graham Jackson
- Advance Forensic Science, St. Andrews, Scotland, UK; School of Science, Engineering and Technology, Abertay University, Dundee, Scotland, UK
| | - Ian W Evett
- Principal Forensic Services Ltd., 34 Southborough Road, Bickley, Bromley, Kent BR1 2EB, UK
| | - Christophe Champod
- Ecole des Sciences Criminelles, Faculty of Law, Criminal Justice and Public Administration, Université de Lausanne, Batochime - Quartier Sorge, CH-1015 Lausanne-Dorigny, Switzerland
| | | | - James M Curran
- Department of Statistics, University of Auckland, PB 92019, Auckland, New Zealand
| | - Duncan Taylor
- Forensic Science South Australia, 21 Divett Place, Adelaide, SA 5000, Australia; School of Biological Sciences, Flinders University, GPO Box 2100, Adelaide, SA 5001, Australia
| | - Bruce S Weir
- University of Washington, Department of Biostatistics, Seattle, WA 98195, United States
| | - Michael D Coble
- National Institute of Standards and Technology, Applied Genetics Group, 100 Bureau Drive, Gaithersburg, MD 20899, United States; Center for Human Identification, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX 76107, United States
| | - John S Buckleton
- University of Washington, Department of Biostatistics, Seattle, WA 98195, United States; Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland 1142, New Zealand
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19
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Ommen DM, Saunders CP, Neumann C. The characterization of Monte Carlo errors for the quantification of the value of forensic evidence. J STAT COMPUT SIM 2017. [DOI: 10.1080/00949655.2017.1280036] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Danica M. Ommen
- Department of Mathematics and Statistics, South Dakota State University, Brookings, SD, USA
| | | | - Cedric Neumann
- Department of Mathematics and Statistics, South Dakota State University, Brookings, SD, USA
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20
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21
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Abstract
This article is a response to the position papers published in the Science & Justice virtual special issue on measuring and reporting the precision of forensic likelihood ratios. I point out a number of serious statistical errors in some of these papers. These issues need to be properly addressed before the philosophical debate can be conducted in earnest.
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Affiliation(s)
- A Philip Dawid
- Statistical Laboratory, University of Cambridge, Wilberforce Road, Cambridge CB3 0WB, UK.
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22
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Use of relevant data, quantitative measurements, and statistical models to calculate a likelihood ratio for a Chinese forensic voice comparison case involving two sisters. Forensic Sci Int 2016; 267:115-124. [DOI: 10.1016/j.forsciint.2016.08.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2016] [Revised: 08/02/2016] [Accepted: 08/08/2016] [Indexed: 11/23/2022]
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