Using the likelihood ratio in bloodstain pattern analysis

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2022-01
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Champod, Christophe
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© 2021 The Authors. Journal of Forensic Sciences published by Wiley Periodicals LLC on behalf of American Academy of Forensic Sciences.1Struo LLC, Ames, Iowa, USA2Department of Statistics, Iowa State University, Ames, Iowa, USA3Department of Industrial Manufacturing & Systems Engineering, Iowa State University, Ames, Iowa, USA4Ecole des Sciences Criminelles, Faculty of Law, Criminal Justice and Public Administration, Université de Lausanne, Lausanne, SwitzerlandCorrespondenceDaniel Attinger, PhD, Struo LLC, 1908 Northwestern ave, Ames, IA 50010, USA.Email: daniel.attinger@gmail.comKris De Brabanter, PhD, Department of Statistics, Iowa State University, 2419 Snedecor Hall, 2438 Osborn Dr. Ames, IA 50011-1210, USA.Email: kbrabant@iastate.eduFunding informationKDB acknowledges funding by the Center for Statistics and Applications in Forensic Evidence (CSAFE) through Cooperative Agreement 70NANB20H019 between NIST and Iowa State University, which includes activities carried out at Carnegie Mellon University, Duke University, University of California Irvine, University of Virginia, West Virginia University, University of Pennsylvania, Swarthmore College, and University of Nebraska, Lincoln.AbstractThere is an apparent paradox that the likelihood ratio (LR) approach is an appropriate measure of the weight of evidence when forensic findings have to be evaluated in court, while it is typically not used by bloodstain pattern analysis (BPA) experts. This commentary evaluates how the scope and methods of BPA relate to several types of evaluative propositions and methods to which LRs are applicable. As a result of this evaluation, we show how specificities in scope (BPA being about activities rather than source identification), gaps in the underlying science base, and the reliance on a wide range of methods render the use of LRs in BPA more complex than in some other forensic disciplines. Three directions are identified for BPA research and train-ing, which would facilitate and widen the use of LRs: research in the underlying phys-ics; the development of a culture of data sharing; and the development of training material on the required statistical background. An example of how recent fluid dy-namics research in BPA can lead to the use of LR is provided. We conclude that an LR framework is fully applicable to BPA, provided methodic efforts and significant developments occur along the three outlined directions.KEYWORDSblood, bloodstain pattern analysis, courtroom testimony, likelihood ratio, statisticsHighlights• The likelihood ratio is rarely used in bloodstain pattern analysis (BPA), even though this is a useful measure of the weight of forensic evidence.• This shortcoming is attributed to specificities in scope and methods and to gaps in the under-lying science base.• Three lines of efforts in research and training are recommended to promote the use of likeli-hood ratios in BPA.• We describe how to estimate a likelihood ratio relevant to BPA, based on recent fluid dynam-ics research.1 | INTRODUCTIONIn evaluative reporting, there is a current trend to evaluate findings based on the concept of likelihood ratio (LR). Recent guidelines rec-ommending the use of LR have been issued by the UK Association of Forensic Science Providers (AFSP) [1], then adapted by the European Network of Forensic Science Institutes [2], the National Institute of Forensic Science, Australia and New Zealand (NIFS) [3], and recently advised by the UK Forensic Science Regulator (FSR), the UK Charted Society of Forensic Science, and the Royal
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Statistics

The Department of Statistics seeks to teach students in the theory and methodology of statistics and statistical analysis, preparing its students for entry-level work in business, industry, commerce, government, or academia.

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The Department of Statistics was formed in 1948, emerging from the functions performed at the Statistics Laboratory. Originally included in the College of Sciences and Humanities, in 1971 it became co-directed with the College of Agriculture.

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Center for Statistics and Applications in Forensic Evidence
The Center for Statistics and Applications in Forensic Evidence (CSAFE) carries out research on the scientific foundations of forensic methods, develops novel statistical methods and transfers knowledge and technological innovations to the forensic science community. We collaborate with more than 80 researchers and across six universities to drive solutions to support our forensic community partners with accessible tools, open-source databases and educational opportunities.
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Industrial and Manufacturing Systems Engineering
The Department of Industrial and Manufacturing Systems Engineering teaches the design, analysis, and improvement of the systems and processes in manufacturing, consulting, and service industries by application of the principles of engineering. The Department of General Engineering was formed in 1929. In 1956 its name changed to Department of Industrial Engineering. In 1989 its name changed to the Department of Industrial and Manufacturing Systems Engineering.
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There is an apparent paradox that the likelihood ratio (LR) approach is an appropriate measure of the weight of evidence when forensic findings have to be evaluated in court, while it is typically not used by bloodstain pattern analysis (BPA) experts. This commentary evaluates how the scope and methods of BPA relate to several types of evaluative propositions and methods to which LRs are applicable. As a result of this evaluation, we show how specificities in scope (BPA being about activities rather than source identification), gaps in the underlying science base, and the reliance on a wide range of methods render the use of LRs in BPA more complex than in some other forensic disciplines. Three directions are identified for BPA research and training, which would facilitate and widen the use of LRs: research in the underlying physics; the development of a culture of data sharing; and the development of training material on the required statistical background. An example of how recent fluid dynamics research in BPA can lead to the use of LR is provided. We conclude that an LR framework is fully applicable to BPA, provided methodic efforts and significant developments occur along the three outlined directions.
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The following is published as Attinger, Daniel, Kris De Brabanter, and Christophe Champod. "Using the likelihood ratio in bloodstain pattern analysis." Journal of forensic sciences 67, no. 1 (2022): 33-43. Posted with permission of CSAFE. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited
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