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Using the likelihood ratio in bloodstain pattern analysis
Authors:Daniel Attinger  Kris De Brabanter  Christophe Champod
Institution:1. Department of Statistics, Iowa State University, Ames, Iowa, USA;2. Department of Industrial Manufacturing & Systems Engineering, Iowa State University, Ames, Iowa, USA;3. Daniel Attinger, PhD, Struo LLC, 1908 Northwestern ave, Ames, IA 50010, USA.;4. Email: daniel.attinger@gmail.com;5. Kris De Brabanter, PhD, Department of Statistics, Iowa State University, 2419 Snedecor Hall, 2438 Osborn Dr. Ames, IA 50011-1210, USA.;6. Email: kbrabant@iastate.eduSearch for more papers by this authorChristophe Champod PhD,
First published: 29 October 2021
Funding information: ;7. KDB 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.
Abstract: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.
Keywords:blood  bloodstain pattern analysis  courtroom testimony  likelihood ratio  statistics
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