Time filter

Source Type

Ansell R.,The Swedish National Laboratory of Forensic Science | Ansell R.,Linköping University
Accreditation and Quality Assurance | Year: 2013

The trail from initial evidence examination to a DNA profile reported to match a suspect is long and complex. The different nature and great variability in the biological and DNA evidence to be recovered and analyzed, add to this complexity. Internal quality controls play an important role in maintaining a high-quality performance in daily forensic biology and DNA profiling practice. In many cases are empirical rather than analytical approaches adopted. Obviously, despite the fact of being necessary, the internal quality controls performed still need to be kept rational at a limited, yet acceptable level. Quality control from a forensic biology and DNA profiling horizon has a wider context and does not only concern obvious fit-for-purpose verifications of analytical processes, chemicals, or reagents in daily routine practice. It also includes control on computerized laboratory management and expert systems, laboratory environmental DNA monitoring, and the use of elimination DNA databases. In addition, a structured recording and handling of non-conformances and "near failures" is essential. Proper management of the non-conformances supports continuous quality improvements by learning from the errors occurring in daily practice. High transparency of non-conformances is important not only for internal improvements, but also for the criminal justice system as well as to maintain public confidence and trust. Together the quality controls used aim at maintaining evidence and DNA sample integrity and to accomplish correct results and interpretations by verifying that methods used data transfers and interpretations made are correct and performed according to validated and accredited conditions. © 2013 Springer-Verlag Berlin Heidelberg.


Nordgaard A.,The Swedish National Laboratory of Forensic Science | Nordgaard A.,Linköping University | Hoglund T.,The Swedish National Laboratory of Forensic Science
Journal of Forensic Sciences | Year: 2011

A reported likelihood ratio for the value of evidence is very often a point estimate based on various types of reference data. When presented in court, such frequentist likelihood ratio gets a higher scientific value if it is accompanied by an error bound. This becomes particularly important when the magnitude of the likelihood ratio is modest and thus is giving less support for the forwarded proposition. Here, we investigate methods for error bound estimation for the specific case of digital camera identification. The underlying probability distributions are continuous and previously proposed models for those are used, but the derived methodology is otherwise general. Both asymptotic and resampling distributions are applied in combination with different types of point estimators. The results show that resampling is preferable for assessment based on asymptotic distributions. Further, assessment of parametric estimators is superior to evaluation of kernel estimators when background data are limited. © 2011 American Academy of Forensic Sciences.


PubMed | The Swedish National Laboratory of Forensic Science
Type: Journal Article | Journal: Journal of forensic sciences | Year: 2011

A reported likelihood ratio for the value of evidence is very often a point estimate based on various types of reference data. When presented in court, such frequentist likelihood ratio gets a higher scientific value if it is accompanied by an error bound. This becomes particularly important when the magnitude of the likelihood ratio is modest and thus is giving less support for the forwarded proposition. Here, we investigate methods for error bound estimation for the specific case of digital camera identification. The underlying probability distributions are continuous and previously proposed models for those are used, but the derived methodology is otherwise general. Both asymptotic and resampling distributions are applied in combination with different types of point estimators. The results show that resampling is preferable for assessment based on asymptotic distributions. Further, assessment of parametric estimators is superior to evaluation of kernel estimators when background data are limited.

Loading The Swedish National Laboratory of Forensic Science collaborators
Loading The Swedish National Laboratory of Forensic Science collaborators