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. 2024 Nov 5;121(45):e2315431121.
doi: 10.1073/pnas.2315431121. Epub 2024 Oct 28.

Incorrect statistical reasoning in Guyll et al. leads to biased claims about strength of forensic evidence

Michael Rosenblum  1 , Elizabeth T Chin  1 , Elizabeth L Ogburn  1 , Akihiko Nishimura  1 , Daniel Westreich  2 , Abhirup Datta  1 , Susan Vanderplas  3 , Maria Cuellar  4   5 , William C Thompson  6
Affiliations

Incorrect statistical reasoning in Guyll et al. leads to biased claims about strength of forensic evidence

Michael Rosenblum et al. Proc Natl Acad Sci U S A. .
No abstract available

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Conflict of interest statement

Competing interests statement:M.R. is an expert witness for the D.C. Public Defender Service and is paid for his work on the case, but no such funding was used to support the work on this manuscript. M.R.’s work as expert witness is through the consulting company Evolution Trial Design, Inc. of which he is co-owner and president. W.C.T. is an expert witness for the Innocence Project, which is involved in the same case as Amicus Curiae.

Figures

Fig. 1.
Fig. 1.
Reproduced from ref. : The above plot shows how posterior probabilities (vertical axis) are highly dependent on assumptions about the prior (horizontal axis). The horizontal axis represents the number n of guns in a simplified scenario with n possible guns and where the prior probability of same source ground truth is assumed to be 1/n. We are not suggesting to base the prior odds solely on the number of possible firearms, rather using it to illustrate sensitivity of the posterior to the choice of prior.
See this image and copyright information in PMC

References

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    1. D. C. Superior Court, Transcript. Superior Court of the District of Columbia Criminal Division (Criminal Action No. 2018-CF1-4356, Official Court Reporter Kristin Clark, Washington, D.C., 2023), pp. 66–80, July 14, 2023.
    1. Rosenblum M., et al. , Misuse of statistical method results in highly biased interpretation of forensic evidence in Guyll et al. (2023). Law Probab. Risk 23, mgad010 (2024).
    1. Gauvrit N., Morsanyi K., The equiprobability bias from a mathematical and psychological perspective. Adv. Cogn. Psychol. 10, 119–130 (2014). - PMC - PubMed
    1. Friedman R. D., A presumption of innocence, not of even odds. Stanford Law Rev. 52, 873 (2000).