Current challenges in statistical DNA evidence evaluation

Cereda, G. (2017)

Doctoral Thesis

This thesis covers different problems concerning the evaluation of DNA evidence. It is mainly divided into two parts: the
first regards the DIP-STR genotyping techniques. It addresses the imperative need of developing a model to assign the likelihood ratio for DIP-STR results, and compares, from a statistical and forensic perspective, the advantages of this novel marker system compared to traditional marker systems, such as STR and Y-STR.
The second part deals with several more general statistical aspects involved in the evaluation of DNA evidence. It aims at defining the differences between full Bayesian methods and ad
hoc plug-in approximations, and at solving the rare type match problem for Y-STR data.
The issues of the different reductions of data and of the levels of uncertainty involved in frequentist solutions are also discussed.
These two parts are connected in the
final project, by developing a Bayesian solution for the rare type match problem for DIP-STR marker system. Moreover, the initial model for DIP-STR data is improved in the light of the statistical discussion of the second part: any ad hoc solution is avoided to obtain a full Bayesian approach.

• DNA evidence evaluation
• Bayesian statistics
• Y-STR haplotypes
• Rare type match

• All authors: Cereda, G.
• Supervisor: Gill, R.D.; Taroni, F.
• Committee: Vaart, A.W. van der; Grünwald, P.; Biedermann, A.; Mortera, J.; Sjerps, M.
• Qualification: Doctor (dr.)
• Awarding Institution: Institute of Mathematics, Science, Leiden University
• Date: 2017-01-12