Are low LRs reliable?

John S Buckleton; Simone N Pugh; Jo-Anne Bright; Duncan A Taylor; James M Curran; Maarten Kruijver; Peter Gill; Bruce Budowle; Kevin Cheng

doi:10.1016/j.fsigen.2020.102350

Are low LRs reliable?

Forensic Sci Int Genet. 2020 Nov:49:102350. doi: 10.1016/j.fsigen.2020.102350. Epub 2020 Jul 8.

Authors

John S Buckleton¹, Simone N Pugh², Jo-Anne Bright³, Duncan A Taylor⁴, James M Curran⁵, Maarten Kruijver³, Peter Gill⁶, Bruce Budowle⁷, Kevin Cheng⁸

Affiliations

¹ University of Auckland, Department of Statistics, Private Bag 92019, Auckland, New Zealand; Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142 New Zealand. Electronic address: john.buckleton@esr.cri.nz.
² California Department of Justice, Redding, CA, USA.
³ Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142 New Zealand.
⁴ Forensic Science South Australia, 21 Divett Place, Adelaide, SA 5000, Australia; School of Biological Sciences, Flinders University, GPO Box 2100 Adelaide SA, Australia.
⁵ Department of Clinical Medicine, University of Oslo, Norway.
⁶ Department of Clinical Medicine, University of Oslo, Norway; Forensic Genetics Research Group, Oslo University Hospital, Oslo, Norway.
⁷ Center for Human Identification, Department of Microbiology, Immunology, and Genetics, University of North Texas Health Science Center, 3500 Camp Bowie Blvd., Fort Worth, TX, 76107, USA.
⁸ University of Auckland, Department of Statistics, Private Bag 92019, Auckland, New Zealand; Institute of Environmental Science and Research Limited, Private Bag 92021, Auckland, 1142 New Zealand.

PMID: 32979624
DOI: 10.1016/j.fsigen.2020.102350

Abstract

To answer the question "Are low likelihood ratios reliable?" requires both a definition of reliable and then a test of whether low likelihood ratios (LRs) meet that definition. We offer, from a purely statistical standpoint, that reliability can be determined by assessing whether the rate of inclusionary support for non-donors over many cases is not larger than expected from the LR value. Thus, it is not the magnitude of the LR alone that determines reliability. Turing's rule is used to inform the expected rate of non-donor inclusionary support, where the rate of non-donor inclusionary support is at most the reciprocal of the LR, i.e. Pr(LR > x|H_a) ≤1/x. There are parallel concerns about whether the value of the evidence can be communicated. We do not discuss that in depth here although it is an important consideration to be addressed with training. In this paper, we use a mixture of real and simulated data to show that the rate of non-donor inclusionary support for these data is significantly lower than the upper bound given by Turing's rule. We take this as strong evidence that low LRs are reliable.

Keywords: Forensic DNA; Likelihood ratio; Probabilistic genotyping; STRmix.

Publication types

Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

DNA / genetics*
DNA Fingerprinting*
Humans
Likelihood Functions*
Microsatellite Repeats
Reproducibility of Results

Substances

DNA