Tacha Hicks

ASSESSING TRANSFER PROBABILITIES IN A BAYESIAN INTERPRETATION OF FORENSIC GLASS EVIDENCE

When someone breaks glass a number of tiny fragments may be transferred to that person. If the glass is broken in the commission of a crime then these fragments may be used as evidence. A Bayesian interpretation of this evidence relies on the forensic scientists ability to assess the probability of transfer. This paper examines the problem of assessing this probability and suggests some solutions.

Use of DNA profiles for investigation using a simulated national DNA database: Part I. Partial SGM Plus® profiles

In traditional criminal investigation, uncertainties are often dealt with using a combination of common sense, practical considerations and experience, but rarely with tailored statistical models. For example, in some countries, in order to search for a given profile in the national DNA database, it must have allelic information for six or more of the ten SGM Plus loci for a simple trace. If the profile does not have this amount of information then it cannot be searched in the national DNA database (NDNAD). This requirement (of a result at six or more loci) is not based on a statistical approach, but rather on the feeling that six or more would be sufficient. A statistical approach, however, could be more rigorous and objective and would take into consideration factors such as the probability of adventitious matches relative to the actual database size and/or investigators requirements in a sensible way. Therefore, this research was undertaken to establish scientific foundations pertaining to the use of partial SGM Plus loci profiles (or similar) for investigation.

Evaluating forensic biology results given source level propositions

The evaluation of forensic evidence can occur at any level within the hierarchy of propositions depending on the question being asked and the amount and type of information that is taken into account within the evaluation. Commonly DNA evidence is reported given propositions that deal with the sub-source level in the hierarchy, which deals only with the possibility that a nominated individual is a source of DNA in a trace (or contributor to the DNA in the case of a mixed DNA trace). We explore the use of information obtained from examinations, presumptive and discriminating tests for body fluids, DNA concentrations and some case circumstances within a Bayesian network in order to provide assistance to the Courts that have to consider propositions at source level. We use a scenario in which the presence of blood is of interest as an exemplar and consider how DNA profiling results and the potential for laboratory error can be taken into account. We finish with examples of how the results of these reports could be presented in court using either numerical values or verbal descriptions of the results.

Using sensitivity analyses in Bayesian Networks to highlight the impact of data paucity and direct future analyses: a contribution to the debate on measuring and reporting the precision of likelihood ratios

Bayesian networks are being increasingly used to address complex questions of forensic interest. Like all probabilities, those that underlie the nodes within a network rely on structured data and knowledge. Obviously, the more structured data we have, the better. But, in real life, the numbers of experiments that can be carried out are limited. It is thus important to know if/when our knowledge is sufficient and when one needs to perform further experiments to be in a position to report the value of the observations made. To explore the impact of the amount of data that are available for assessing results, we have constructed Bayesian Networks and explored the sensitivity of the likelihood ratios to changes to the data that underlie each node. Bayesian networks are constructed and sensitivity analyses performed using freely available R libraries (gRain and BNlearn). We demonstrate how the analyses can be used to yield information about the robustness provided by the data used to inform the conditional probability table, and also how they can be used to direct further research for maximum effect. By maximum effect, we mean to contribute with the least investment to an increased robustness. In addition, the paper investigates the consequences of the sensitivity analysis to the discussion on how the evidence shall be reported for a given state of knowledge in terms of underpinning data.

Helping to distinguish primary from secondary transfer events for trace DNA

DNA is routinely recovered in criminal investigations. The sensitivity of laboratory equipment and DNA profiling kits means that it is possible to generate DNA profiles from very small amounts of cellular material. As a consequence, it has been shown that DNA we detect may not have arisen from a direct contact with an item, but rather through one or more intermediaries. Naturally the questions arising in court, particularly when considering trace DNA, are of how DNA may have come to be on an item. While scientists cannot directly answer this question, forensic biological results can help in discriminating between alleged activities. Much experimental research has been published showing the transfer and persistence of DNA under varying conditions, but as of yet the results of these studies have not been combined to deal with broad questions about transfer mechanisms. In this work we use published data and Bayesian networks to develop a statistical logical framework by which questions of transfer mechanism can be approached probabilistically. We also identify a number of areas where further work could be carried out in order to improve our knowledge base when helping to address questions about transfer mechanisms. Finally, we apply the constructed Bayesian network to ground truth known data to determine if, with current knowledge, there is any power in DNA quantities to distinguish primary and secondary transfer events.

Evaluation of Forensic DNA Traces When Propositions of Interest Relate to Activities: Analysis and Discussion of Recurrent Concerns

When forensic scientists evaluate and report on the probative strength of single DNA traces, they commonly rely on only one number, expressing the rarity of the DNA profile in the population of interest. This is so because the focus is on propositions regarding the source of the recovered trace material, such as “the person of interest is the source of the crime stain.” In particular, when the alternative proposition is “an unknown person is the source of the crime stain,” one is directed to think about the rarity of the profile. However, in the era of DNA profiling technology capable of producing results from small quantities of trace material (i.e., non-visible staining) that is subject to easy and ubiquitous modes of transfer, the issue of source is becoming less central, to the point that it is often not contested. There is now a shift from the question “whose DNA is this?” to the question “how did it get there?” As a consequence, recipients of expert information are now very much in need of assistance with the evaluation of the meaning and probative strength of DNA profiling results when the competing propositions of interest refer to different activities. This need is widely demonstrated in day-to-day forensic practice and is also voiced in specialized literature. Yet many forensic scientists remain reluctant to assess their results given propositions that relate to different activities. Some scientists consider evaluations beyond the issue of source as being overly speculative, because of the lack of relevant data and knowledge regarding phenomena and mechanisms of transfer, persistence and background of DNA. Similarly, encouragements to deal with these activity issues, expressed in a recently released European guideline on evaluative reporting (Willis et al., 2015), which highlights the need for rethinking current practice, are sometimes viewed skeptically or are not considered feasible. In this discussion paper, we select and discuss recurrent skeptical views brought to our attention, as well as some of the alternative solutions that have been suggested. We will argue that the way forward is to address now, rather than later, the challenges associated with the evaluation of DNA results (from small quantities of trace material) in light of different activities to prevent them being misrepresented in court.

Helping formulate propositions in forensic DNA analysis

The Bayesian paradigm is the preferred approach to evidence interpretation. It requires the evaluation of the probability of the evidence under at least two propositions. The value of the findings (i.e., our LR) will depend on these propositions and the case information, so it is crucial to identify which propositions are useful for the case at hand. Previously, a number of principles have been advanced and largely accepted for the evaluation of evidence. In the evaluation of traces involving DNA mixtures there may be more than two propositions possible. We apply these principles to some exemplar situations. We also show that in some cases, when there are no clear propositions or no defendant, a forensic scientist may be able to generate explanations to account for observations. In that case, the scientist plays a role of investigator, rather than evaluator. We believe that it is helpful for the scientist to distinguish those two roles.

Discussion on how to implement a verbal scale in a forensic laboratory: Benefits, pitfalls and suggestions to avoid misunderstandings

In a recently published guideline for evaluative reporting in forensic science, the European Network of Forensic Science Institutes (ENFSI) recommended the use of the likelihood ratio for the measurement of the value of forensic results. As a device to communicate the probative value of the results, the ENFSI guideline mentions the possibility to define and use a verbal scale, which should be unified within a forensic institution. This paper summarizes discussions held between scientists of our institution to develop and implement such a verbal scale. It intends to contribute to general discussions likely to be faced by any forensic institution that engages in continuous monitoring and improving of their evaluation and reporting format. We first present published arguments in favour of the use of such verbal qualifiers. We emphasise that verbal qualifiers do not replace the use of numbers to evaluate forensic findings, but are useful to communicate the probative value, since the weight of evidence in terms of likelihood ratio are still apprehended with difficulty by both the forensic scientists, especially in the absence of hard data, and the recipient of information. We further present arguments that support the development of the verbal scale that we propose. Recognising the limits of the use of such a verbal scale, we then discuss its disadvantages: it may lead to the spurious view according to which the value of the observations made in a given case is relative to other cases. Verbal qualifiers are also prone to misunderstandings and cannot be coherently combined with other evidence. We therefore recommend not using the verbal qualifier alone in a written statement. While scientists should only report on the probability of the findings - and not on the probability of the propositions, which are the duty of the Court - we suggest showing examples to let the recipient of information understand how the scientific evidence affects the probabilities of the propositions. To avoid misunderstandings, we also advise to mention in the statement what the results do not mean. Finally, we are of the opinion that if experts were able to coherently articulate numbers, and if recipients of information could properly handle such numbers, then verbal qualifiers could be abandoned completely. At that time, numerical expressions of probative value will be appropriately understood, as other numerical measures that most of us understand without the need of any further explanation, such as expressions for length or temperature.

A template for constructing Bayesian networks in forensic biology cases when considering activity level propositions

The hierarchy of propositions has been accepted amongst the forensic science community for some time. It is also accepted that the higher up the hierarchy the propositions are, against which the scientist are competent to evaluate their results, the more directly useful the testimony will be to the court. Because each case represents a unique set of circumstances and findings, it is difficult to come up with a standard structure for evaluation. One common tool that assists in this task is Bayesian networks (BNs). There is much diversity in the way that BN can be constructed. In this work, we develop a template for BN construction that allows sufficient flexibility to address most cases, but enough commonality and structure that the flow of information in the BN is readily recognised at a glance. We provide seven steps that can be used to construct BNs within this structure and demonstrate how they can be applied, using a case example.

The Importance of Critically Examining the Level of Propositions When Evaluating Forensic DNA Results.

The proposal of a discussion about the use of software to help assign likelihood ratios for forensic DNA profiling results, and the use of their output in the legal process, is both timely and important (see also related contributions elsewhere in Frontiers, e.g., Biedermann et al., 2014). Ever since their introduction in forensic science, DNA profiling analyses have been accompanied with the results of calculations of various sorts. Their scope is well illustrated and documented in several reference monographs (e.g., Evett and Weir, 1998; Buckleton et al., 2005; Balding and Steele, 2015). This solid body of scholarly research and established practice has contributed to the widely held view among scientists and recipients of expert information that eliciting the probative strength of forensic DNA profiling results is per se a numerical task. In this commentary, we intend—in a first part—to make the point that although calculations are, by virtue, an integral part of the quantification of probative strength, it is equally important at the outset to be clear about the question “Why are we doing a calculation?” (Buckleton et al., 2005, p. 151). We will argue that this is not a question that statistics can answer. Stated otherwise, we will contend that, as much it is important to be clear in any instance about what a particular computation exactly purports to do, it is essential to define the questions that are of interest in a particular case at hand. In a second part, we will emphasize on the extent to which, why and how recently issued guidelines (e.g., ENFSI, 2015) encourage such thinking about cases prior to conducting calculations, if any.