A generalised Bayes' factor formula for evidence evaluation under activity level propositions: Variations around a fibres scenario.

Generalised Bayes' factors and associated Bayesian networks are developed for the transfer of extrinsic evidence at the activity level, developments that extend previous work on activity level evaluation. A strategy for the assessment of extrinsic evidence is developed in stages with progressive increases in complexity. The final development is illustrated with an example involving fibres from clothing.

More on the question 'When does absence of evidence constitute evidence of absence?' How Bayesian confirmation theory can logically support the answer.

In forensic science it is not rare that common sayings are used to support particular inferences. A typical example is the adage 'The absence of evidence is not evidence of absence'. This paper analyzes the rationale hidden behind such statement and it offers a structural way to approach the analysis of this particular adage throughout a careful analysis of four different scenarios.

The subjectivist interpretation of probability and the problem of individualisation in forensic science.

This paper presents and discusses further aspects of the subjectivist interpretation of probability (also known as the 'personalist' view of probabilities) as initiated in earlier forensic and legal literature. It shows that operational devices to elicit subjective probabilities - in particular the so-called scoring rules - provide additional arguments in support of the standpoint according to which categorical claims of forensic individualisation do not follow from a formal analysis under that view of probability theory.

Decision-theoretic analysis of forensic sampling criteria using bayesian decision networks.

Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (bayesian) probabilistic sampling approaches. These are now widely implemented in practice.

Uncertainty about the true source. A note on the likelihood ratio at the activity level.

This paper focuses on likelihood ratio based evaluations of fibre evidence in cases in which there is uncertainty about whether or not the reference item available for analysis - that is, an item typically taken from the suspect or seized at his home - is the item actually worn at the time of the offence. A likelihood ratio approach is proposed that, for situations in which certain categorical assumptions can be made about additionally introduced parameters, converges to formula described in existing literature. The properties of the proposed likelihood ratio approach are analysed through sensitivity analyses and discussed with respect to possible argumentative implications that arise in practice.

Equal prior probabilities: can one do any better?

This paper discusses recommendations concerning the use of prior probabilities that underlie recent, but in no way novel, proposals of presenting scientific evidence in terms of posterior probabilities, in the context sometimes referred to as the 'full Bayes' approach'. A chief issue of this procedure is a proposal that--given the unavailability of case-specific circumstantial information--scientists should consider the prior probabilities of the propositions under which scientific evidence is evaluated as equal. The discussion presented here draws the reader's attention to the fact that the philosophical foundations of such a recommendation (in particular, attempted justifications through the Principle of Maximum Entropy (PME)) are far more controversial than what is actually admitted by the advocates for their use in the theory and practice of forensic science.

A general approach to Bayesian networks for the interpretation of evidence.

Bayesian networks (BNs) are mathematically and statistically rigorous techniques for handling uncertainty. The field of forensic science has recently attributed increased attention to the many advantages of this graphical method for assisting the evaluation of scientific evidence. However, the majority of contributions that relate to this topic restrict themselves to the presentation of already "constructed" BNs, and often, only a few explanations are given as to how one obtains a specific BN structure for a given problem.

A graphical model for the evaluation of cross-transfer evidence in DNA profiles.

The role of graphical models in the assessment of transfer evidence is described with particular reference to the role of cross-transfer evidence. The issues involved in the determination of factors (nodes), associations (links) and probabilities to be included are discussed. Four types of subjective probabilities are of particular interest: those for transfer, persistence and recovery; innocent acquisition; relevance; innocent presence.

Evaluation of scientific evidence using Bayesian networks.

Bayesian networks provide a valuable aid for representing epistemic relationships in a body of uncertain evidence. The paper proposes some simple Bayesian networks for standard analysis of patterns of inference concerning scientific evidence, with a discussion of the rationale behind the nets, the corresponding probabilistic formulas, and the required probability assessments.