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Likelihood Ratio as Weight of Forensic Evidence: A Closer Look

Published

Author(s)

Hariharan K. Iyer, Steven P. Lund

Abstract

The forensic science community has increasingly sought quantitative methods for conveying the weight of evidence. Experts from many forensic laboratories summarize their fndings in terms of a likelihood ratio. Several proponents of this approach have argued that Bayesian reasoning proves it to be normative. We fnd this likelihood ratio paradigm to be unsupported by arguments of Bayesian decision theory, which applies only to personal decision making and not to the transfer of information from an expert to a separate decision maker. We further argue that decision theory does not exempt the presentation of a likelihood ratio from uncertainty characterization, which is required to assess the ftness for purpose of any transferred quantity. We propose the concept of a lattice of assumptions leading to an uncertainty pyramid as a framework for assessing the uncertainty in an evaluation of a likelihood ratio. We demonstrate the use of these concepts with illustrative examples regarding the refractive index of glass and automated comparison scores for fngerprints.
Citation
Journal of Research (NIST JRES) -
Volume
122

Keywords

assumptions lattice, Bayes’ factor, Bayes’ rule, Bayesian decision theory, subjective probability, uncertainty, uncertainty pyramid.

Citation

Iyer, H. and Lund, S. (2017), Likelihood Ratio as Weight of Forensic Evidence: A Closer Look, Journal of Research (NIST JRES), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/jres.122.027 (Accessed May 13, 2021)
Created October 12, 2017, Updated January 27, 2020