An overview of log likelihood ratio cost in forensic science - Where is it used and what values can we expect?

There is increasing support for reporting evidential strength as a likelihood ratio (LR) and increasing interest in (semi-)automated LR systems. The log-likelihood ratio cost () is a popular metric for such systems, penalizing misleading LRs further from 1 more.  = 0 indicates perfection while  = 1 indicates an uninformative system.

From data to a validated score-based LR system: A practitioner's guide.

Likelihood ratios (LRs) are a useful measure of evidential strength. In forensic casework consisting of a flow of cases with essentially the same question and the same analysis method, it is feasible to construct an 'LR system', that is, an automated procedure that has the observations as input and an LR as output. This paper is aimed at practitioners interested in building their own LR systems.

The evidential strength of a combination of corresponding class features in tire examination.

Tire marks are an important type of forensic evidence as they are frequently encountered at crime scenes. When the tires of a suspect's car are compared, the evidence can be very strong if so-called 'acquired features' are observed to correspond. When only 'class characteristics' such as parts of the tire pattern are observed to correspond, it is obvious that many other tires will exist that also correspond, and so this evidence is usually considered very weak or is simply ignored.

Evidential value of duct tape comparison using loopbreaking patterns.

A new method for the evaluation of duct tape ends is proposed. This method is based on the breaks of the loops in the warp yarns, when duct tape with a scrim of chain-stitched warp yarns and weft-insertion is torn. After tearing, the loop at the end of each warp yarn can be in one of four states: open, closed, complex or missing.

The logic of forensic pathology opinion.

Evaluating evidence and providing opinions are at the heart of forensic science, and forensic experts are expected to provide opinions that are based on logically sound and transparent scientific reasoning, and that honour the boundaries of their area of expertise. In order to meet these objectives, many fields of science explicitly apply Bayes' theorem, which describes the logically correct way to update probabilities on the basis of observations. Making a distinction between 'investigative' and evaluative' modes of operating helps to implement the theorem into daily casework.

Measuring calibration of likelihood-ratio systems: A comparison of four metrics, including a new metric devPAV.

Numerical likelihood-ratio (LR) systems aim to calculate evidential strength for forensic evidence evaluation. Calibration of such LR-systems is essential: one does not want to over- or understate the strength of the evidence. Metrics that measure calibration differ in sensitivity to errors in calibration of such systems.

Why calibrating LR-systems is best practice. A reaction to "The evaluation of evidence for microspectrophotometry data using functional data analysis", in FSI 305.

In their paper "The evaluation of evidence for microspectrophotometry data using functional data analysis", in FSI 305, Aitken et al. present a likelihood-ratio (LR) system for their data. We show the values generated by this system cannot be interpreted as LRs: they are ill-calibrated and should be interpreted as discriminating scores.

Combining evidence in complex cases - a practical approach to interdisciplinary casework.

Activity level evaluations, although still a major challenge for many disciplines, bring a wealth of possibilities for a more formal approach to the evaluation of interdisciplinary forensic evidence. This paper proposes a practical methodology for combining evidence from different disciplines within the likelihood ratio framework. Evidence schemes introduced in this paper make the process of combining evidence more insightful and intuitive thereby assisting experts in their interdisciplinairy evaluation and in explaining this process to the courts.

Targeting relevant sampling areas for human biological traces: Where to sample displaced bodies for offender DNA?

Sampling strategy is one of the deciding factors in DNA typing success rates. Small amounts of bodily fluid traces and (skin) contact traces are currently not visualized in standard forensic practice. Trace recovery is usually based on the information available in a particular case and on the experience and 'forensic common sense' applied by the trace recovery expert.

Evaluating evidence in linked crimes with multiple offenders.

In de Zoete et al. (2015) a framework for the evaluation of evidence when an individual is a suspect of two separate offenses (based on Evett et al., 2006) is implemented using a Bayesian network.

Performance Study of a Score-based Likelihood Ratio System for Forensic Fingermark Comparison.

In this article, the performance of a score-based likelihood ratio (LR) system for comparisons of fingerprints with fingermarks is studied. The system is based on an automated fingerprint identification system (AFIS) comparison algorithm and focuses on fingerprint comparisons where the fingermarks contain 6-11 minutiae. The hypotheses under consideration are evaluated at the level of the person, not the finger.

Cell type determination and association with the DNA donor.

In forensic casework, evidence regarding the type of cell material contained in a stain can be crucial in determining what happened. For example, a DNA match in a sexual offense can become substantially more incriminating when there is evidence supporting that semen cells are present. Besides the question which cell types are present in a sample, also the question who donated what (association) is very relevant.

Leveraging probabilistic peak detection to estimate baseline drift in complex chromatographic samples.

Accurate analysis of chromatographic data often requires the removal of baseline drift. A frequently employed strategy strives to determine asymmetric weights in order to fit a baseline model by regression. Unfortunately, chromatograms characterized by a very high peak saturation pose a significant challenge to such algorithms.

A probabilistic approach for the interpretation of RNA profiles as cell type evidence.

DNA profiles can be used as evidence to distinguish between possible donors of a crime stain. In some cases, both the prosecution and the defence claim that the cell material was left by the suspect but they dispute which cell type was left behind. For example, in sexual offense cases the prosecution could claim that the sample contains semen cells where the defence argues that the sample contains skin cells.

Class-conditional feature modeling for ignitable liquid classification with substantial substrate contribution in fire debris analysis.

Forensic chemical analysis of fire debris addresses the question of whether ignitable liquid residue is present in a sample and, if so, what type. Evidence evaluation regarding this question is complicated by interference from pyrolysis products of the substrate materials present in a fire. A method is developed to derive a set of class-conditional features for the evaluation of such complex samples.

Modelling crime linkage with Bayesian networks.

When two or more crimes show specific similarities, such as a very distinct modus operandi, the probability that they were committed by the same offender becomes of interest. This probability depends on the degree of similarity and distinctiveness. We show how Bayesian networks can be used to model different evidential structures that can occur when linking crimes, and how they assist in understanding the complex underlying dependencies.

Error rates in forensic DNA analysis: definition, numbers, impact and communication.

Forensic DNA casework is currently regarded as one of the most important types of forensic evidence, and important decisions in intelligence and justice are based on it. However, errors occasionally occur and may have very serious consequences. In other domains, error rates have been defined and published.

The combined evidential value of autosomal and Y-chromosomal DNA profiles obtained from the same sample.

When a Y-chromosomal and a (partial) autosomal DNA profile are obtained from one crime sample, and both profiles match the suspect's profiles, we would like to know the combined evidential value. To calculate the likelihood ratio of observing the autosomal and Y-chromosomal DNA profiles combined, we need to know the conditional random match probability of the observed autosomal DNA profile, given the Y-chromosomal match. We examine this conditional probability in two ways: (1) with a database containing data of 2,085 men and (2) using a simulation model.

Anti-doping researchers should conform to certain statistical standards from forensic science.

Anti-doping is currently viewed as a forensic science. However, close examination shows that the statistical treatment of evidence is inconsistent with that view. Here it is insisted that anti-doping researchers should conform to certain statistical standards from forensic science.

Selection effects and database screening in forensic science.

We argue that it is, in principle, not difficult to deal with selection effects in forensic science. If a suspect is selected through a process that is related to the forensic evidence, then the strength of the evidence will be compensated by very small prior odds. No further correction is necessary.

Shoe print examinations: effects of expectation, complexity and experience.

Even though trace evidence is becoming more and more important in legal cases, only little is known about the influence of task and context factors on comparative judgments. In the present study we investigated how expectations and complexity affect shoe print examinations and to what extent differences exist between beginners and experienced examiners. Twelve examiners assessed similarity between a shoe print and a shoe for eight different cases.

The evidential value in the DNA database search controversy and the two-stain problem.

Does the evidential strength of a DNA match depend on whether the suspect was identified through database search or through other evidence ("probable cause")? In Balding and Donnelly (1995, Journal of the Royal Statistical Society, Series A 158, 21-53) and elsewhere, it has been argued that the evidential strength is slightly larger in a database search case than in a probable cause case, while Stockmarr (1999, Biometrics 55, 671-677) reached the opposite conclusion. Both these approaches use likelihood ratios. By making an excursion to a similar problem, the two-stain problem, we argue in this article that there are certain fundamental difficulties with the use of a likelihood ratio, which can be avoided by concentrating on the posterior odds.