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The likelihood ratio (LR) is a commonly used measure for determining the strength of forensic match evidence. When a forensic expert determines a high LR for DNA found at a crime scene matching the DNA profile of a suspect they typically…

Applications · Statistics 2020-09-21 Norman Fenton , Allan Jamieson , Sara Gomes , Martin Neil

In the Bayesian paradigm for presenting forensic evidence to court, it is recommended that the weight of the evidence be summarized as a likelihood ratio (LR) between two opposing hypotheses of how the evidence could have been produced.…

Applications · Statistics 2013-04-15 Niko Brümmer

Many resources for forensic scholars and practitioners, such as journal articles, guidance documents, and textbooks, address how to make a value of evidence assessment in the form of a likelihood ratio (LR) when deciding between two…

Applications · Statistics 2022-05-11 Steven Lund , Hari Iyer

The likelihood ratio (LR) measures the relative weight of forensic data regarding two hypotheses. Several levels of uncertainty arise if frequentist methods are chosen for its assessment: the assumed population model only approximates the…

Applications · Statistics 2016-12-26 Giulia Cereda

The likelihood ratio (LR) is largely used to evaluate the relative weight of forensic data regarding two hypotheses and for its assessment Bayesian methods are widespread in the forensic field. However, the Bayesian `recipe' for the LR…

Applications · Statistics 2016-04-14 Giulia Cereda

In 2016, the European Network of Forensic Science Institutes (ENFSI) published guidelines for the evaluation, interpretation and reporting of scientific evidence. In the guidelines, ENFSI endorsed the use of the likelihood ratio (LR) as a…

Applications · Statistics 2020-05-25 Nathaniel Garton , Danica Ommen , Jarad Niemi , Alicia Carriquiry

The forensic science community has increasingly sought quantitative methods for conveying the weight of evidence. Experts from many forensic laboratories summarize their findings in terms of a likelihood ratio. Several proponents of this…

Applications · Statistics 2017-04-28 Steven P. Lund , Hari K. Iyer

In this article we provide a rebuttal against the possible perception that a single number, such as the Likelihood Ratio, can provide an objective, authoritative or definitive weight of evidence. We also illustrate the extent to which…

Applications · Statistics 2016-09-21 Steven P. Lund , Hari Iyer

For several decades, legal and scientific scholars have argued that conclusions from forensic examinations should be supported by statistical data and reported within a probabilistic framework. Multiple models have been proposed to quantify…

Applications · Statistics 2019-10-14 Cedric Neumann , Madeline A. Ausdemore

A group of approaches for calculating forensic likelihood ratios first calculates scores which quantify the degree of difference or the degree of similarity between pairs of samples, then converts those scores to likelihood ratios. In order…

Applications · Statistics 2016-12-28 Geoffrey Stewart Morrison

Several authors have explained that the likelihood ratio measures the strength of the evidence represented by observations in statistical problems. This idea works fine when the goal is to evaluate the strength of the available evidence for…

Artificial Intelligence · Computer Science 2013-02-01 Paul-Andre Monney

In many jurisdictions, forensic evidence is presented in the form of categorical statements by forensic experts. Several large-scale performance studies have been performed that report error rates to elucidate the uncertainty associated…

Applications · Statistics 2024-01-04 Rolf JF Ypma

The likelihood ratio is a crucial quantity for statistical inference in science that enables hypothesis testing, construction of confidence intervals, reweighting of distributions, and more. Many modern scientific applications, however,…

High Energy Physics - Phenomenology · Physics 2024-12-11 Shahzar Rizvi , Mariel Pettee , Benjamin Nachman

Messenger RNA (mRNA) profiling can identify body fluids present in a stain, yielding information on what activities could have taken place at a crime scene. To account for uncertainty in such identifications, recent work has focused on…

Applications · Statistics 2022-05-23 R. J. F. Ypma , P. A. Maaskant-van Wijk , R. D. Gill , M. Sjerps , M. van den Berge

In the simple vs composite hypothesis test with a proper prior, the Bayes Factor (BF) is shown to be the posterior mean of the Likelihood Ratio (LR). Therefore, the posterior standard deviation of the LR or rather its posterior cumulative…

Solar and Stellar Astrophysics · Physics 2010-01-28 I. Smith , A. Ferrari

Some large scale inference problems are considered based on using the relative belief ratio as a measure of statistical evidence. This approach is applied to the multiple testing problem. A particular application of this is concerned with…

Statistics Theory · Mathematics 2016-09-22 Michael Evans , Jabed Tomal

Bayesian evidence ratios give a very attractive way of comparing models, and being able to quote the odds on a particular model seems a very clear motivation for making a choice. Jeffreys' scale of evidence is often used in the…

Instrumentation and Methods for Astrophysics · Physics 2020-09-07 Charles Jenkins

This paper develops a Bayesian approach for assessing equivalence and non-inferiority hypotheses in two-arm trials using relative belief ratios. A relative belief ratio is a measure of statistical evidence and can indicate evidence either…

Applications · Statistics 2014-01-20 Saman Muthukumarana , Michael Evans

Both the Bayes factor and the relative belief ratio satisfy the principle of evidence and so can be seen to be valid measures of statistical evidence. Certainly Bayes factors are regularly employed. The question then is: which of these…

Statistics Theory · Mathematics 2024-02-28 Luai Al-Labadi , Ayman Alzaatreh , Michael Evans

We introduce a Bayesian solution for the problem in forensic speaker recognition, where there may be very little background material for estimating score calibration parameters. We work within the Bayesian paradigm of evidence reporting and…

Machine Learning · Statistics 2017-10-03 Niko Brümmer , Albert Swart
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