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  • 1.
    Ahlinder, Jon
    et al.
    Totalförsvarets Forskningsinstitut, FOI, Stockholm, Sweden.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, The Division of Statistics and Machine Learning. Linköping University, Faculty of Arts and Sciences. Swedish National Forensic Centre (NFC), Linköping, Sweden.
    Wiklund Lindström, Susanne
    Totalförsvarets Forskningsinstitut, FOI, Stockholm, Sweden.
    Chemometrics comes to court: evidence evaluation of chem–bio threat agent attacks2015In: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 29, no 5, 267-276 p.Article in journal (Refereed)
    Abstract [en]

    Forensic statistics is a well-established scientific field whose purpose is to statistically analyze evidence in order to support legal decisions. It traditionally relies on methods that assume small numbers of independent variables and multiple samples. Unfortunately, such methods are less applicable when dealing with highly correlated multivariate data sets such as those generated by emerging high throughput analytical technologies. Chemometrics is a field that has a wealth of methods for the analysis of such complex data sets, so it would be desirable to combine the two fields in order to identify best practices for forensic statistics in the future. This paper provides a brief introduction to forensic statistics and describes how chemometrics could be integrated with its established methods to improve the evaluation of evidence in court.

    The paper describes how statistics and chemometrics can be integrated, by analyzing a previous know forensic data set composed of bacterial communities from fingerprints. The presented strategy can be applied in cases where chemical and biological threat agents have been illegally disposed.

  • 2.
    Ansell, Ricky
    et al.
    Linköping University, Department of Physics, Chemistry and Biology, Biology. Linköping University, Faculty of Science & Engineering. Polismyndigheten - Nationellt Forensiskt Centrum.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences. Polismyndigheten - Nationellt Forensiskt Centrum.
    Hedell, Ronny
    Polismyndigheten - Nationellt Forensiskt Centrum.
    Interpretation of DNA Evidence: Implications of Thresholds Used in the Forensic Laboratory2014Conference paper (Other academic)
    Abstract [en]

    Evaluation of forensic evidence is a process lined with decisions and balancing, not infrequently with a substantial deal of subjectivity. Already at the crime scene a lot of decisions have to be made about search strategies, the amount of evidence and traces recovered, later prioritised and sent further to the forensic laboratory etc. Within the laboratory there must be several criteria (often in terms of numbers) on how much and what parts of the material should be analysed. In addition there is often a restricted timeframe for delivery of a statement to the commissioner, which in reality might influence on the work done. The path of DNA evidence from the recovery of a trace at the crime scene to the interpretation and evaluation made in court involves several decisions based on cut-offs of different kinds. These include quality assurance thresholds like limits of detection and quantitation, but also less strictly defined thresholds like upper limits on prevalence of alleles not observed in DNA databases. In a verbal scale of conclusions there are lower limits on likelihood ratios for DNA evidence above which the evidence can be said to strongly support, very strongly support, etc. a proposition about the source of the evidence. Such thresholds may be arbitrarily chosen or based on logical reasoning with probabilities. However, likelihood ratios for DNA evidence depend strongly on the population of potential donors, and this may not be understood among the end-users of such a verbal scale. Even apparently strong DNA evidence against a suspect may be reported on each side of a threshold in the scale depending on whether a close relative is part of the donor population or not. In this presentation we review the use of thresholds and cut-offs in DNA analysis and interpretation and investigate the sensitivity of the final evaluation to how such rules are defined. In particular we show what are the effects of cut-offs when multiple propositions about alternative sources of a trace cannot be avoided, e.g. when there are close relatives to the suspect with high propensities to have left the trace. Moreover, we discuss the possibility of including costs (in terms of time or money) for a decision-theoretic approach in which expected values of information could be analysed.

  • 3.
    Grimvall, Anders
    et al.
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Nordgaard, Anders
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Sjöar och vattendrag i Skåne - går utvecklingen åt rätt håll?2004Report (Other academic)
  • 4.
    Hedman, J.
    et al.
    Lund University.
    Nordgaard, Anders
    National Laboratory of Forensic Sciences, Linkoping.
    Rasmusson, Birgitta
    National Laboratory of Forensic Sciences, Linkoping.
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Molecular genetics .
    Rådström, P
    Lund University.
    Using alternative DNA polymerases to combat PCR inhibitors in crime scene samples2009In: Book of Abstracts, 2009, 139-140 p.Conference paper (Refereed)
  • 5.
    Hedman, Johannes
    et al.
    Lunds Universitet/Lunds Tekniska Högskola.
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Molecular genetics. Linköping University, The Institute of Technology.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    A ranking index for quality assessment of forensic DNA profiles2010In: BMC Research Notes, ISSN 1756-0500, Vol. 3, no 290Article in journal (Refereed)
    Abstract [en]

    Background

    Assessment of DNA profile quality is vital in forensic DNA analysis, both in order to determine the evidentiary value of DNA results and to compare the performance of different DNA analysis protocols. Generally the quality assessment is performed through manual examination of the DNA profiles based on empirical knowledge, or by comparing the intensities (allelic peak heights) of the capillary electrophoresis electropherograms.

    Results

    We recently developed a ranking index for unbiased and quantitative quality assessment of forensic DNA profiles, the forensic DNA profile index (FI) (Hedman et al. Improved forensic DNA analysis through the use of alternative DNA polymerases and statistical modeling of DNA profiles, Biotechniques 47 (2009) 951-958). FI uses electropherogram data to combine the intensities of the allelic peaks with the balances within and between loci, using Principal Components Analysis. Here we present the construction of FI. We explain the mathematical and statistical methodologies used and present details about the applied data reduction method. Thereby we show how to adapt the ranking index for any Short Tandem Repeat-based forensic DNA typing system through validation against a manual grading scale and calibration against a specific set of DNA profiles.

    Conclusions

    The developed tool provides unbiased quality assessment of forensic DNA profiles. It can be applied for any DNA profiling system based on Short Tandem Repeat markers. Apart from crime related DNA analysis, FI can therefore be used as a quality tool in paternal or familial testing as well as in disaster victim identification.

  • 6.
    Hedman, Johannes
    et al.
    Department of Applied Microbiology, Lund University, Sweden.
    Nordgaard, Anders
    Swedish National Laboratory of Forencis Sciences, Linkoping, Sweden.
    Dufva, Charlotte
    National Laboratory of Forensic Sciences, Linkoping, Sweden.
    Rasmusson, Birgitta
    National Laboratory of Forensic Sciences, Linkoping, Sweden.
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Molecular genetics. Linköping University, The Institute of Technology.
    Rådström, Peter
    Department of Applied Microbiology, Lund University, Sweden.
    Synergy between DNA polymerases increases polymerase chain reaction inhibitor tolerance in forensic DNA analysis2010In: Analytical Biochemistry, ISSN 0003-2697, E-ISSN 1096-0309, Vol. 405, 192-200 p.Article in journal (Refereed)
    Abstract [en]

    The success rate of diagnostic polymerase chain reaction (PCR) analysis is lowered by inhibitory substancespresent in the samples. Recently, we showed that tolerance to PCR inhibitors in crime scene salivastains can be improved by replacing the standard DNA polymerase AmpliTaq Gold with alternative DNApolymerase–buffer systems (Hedman et al., BioTechniques 47 (2009) 951–958). Here we show thatblending inhibitor-resistant DNA polymerase–buffer systems further increases the success rate of PCRfor various types of real crime scene samples showing inhibition. For 34 of 42 ‘‘inhibited” crime scenestains, the DNA profile quality was significantly improved using a DNA polymerase blend of ExTaq HotStart and PicoMaxx High Fidelity compared with AmpliTaq Gold. The significance of the results was confirmedby analysis of variance. The blend performed as well as, or better than, the alternative DNA polymerasesused separately for all tested sample types. When used separately, the performance of the DNApolymerases varied depending on the nature of the sample. The superiority of the blend is discussed interms of complementary effects and synergy between the DNA polymerase–buffer systems.

  • 7.
    Hedman, Johannes
    et al.
    Lund University.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Rasmusson, Birgitta
    Linköping University, Department of Clinical and Experimental Medicine, Medical Microbiology. Linköping University, Faculty of Health Sciences.
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Molecular genetics. Linköping University, Faculty of Health Sciences.
    Radstrom, Peter
    Lund University.
    Improved forensic DNA analysis through the use of alternative DNA polymerases and statistical modeling of DNA profiles2009In: BIOTECHNIQUES, ISSN 0736-6205, Vol. 47, no 5, 951-958 p.Article in journal (Refereed)
    Abstract [en]

    DNA evidence, linking perpetrators to crime scenes, is central to many legal proceedings. However, DNA samples from crime scenes often contain PCR-inhibitory substances, which may generate blank or incomplete DNA profiles. Extensive DNA purification can be required to rid the sample of these inhibitors, although these procedures increase the risk of DNA loss. Most forensic laboratories use commercial DNA amplification kits (e.g., AmpFlSTR SGM Plus) with the DNA polymerase AmpliTaq Gold as the gold standard. Here, we show that alternative DNA polymerase-buffer systems can improve the quality of forensic DNA analysis and efficiently circumvent PCR inhibition in crime scene samples, without additional sample preparation. DNA profiles from 20 of 32 totally or partially inhibited crime scene saliva samples were significantly improved using Bio-X-Act Short, ExTaq Hot Start, or PicoMaxx High Fidelity instead of AmpliTaq Gold. A statistical model for unbiased quality control of forensic DNA profiles was developed to quantify the results. Our study demonstrates the importance of adjusting the chemistry of the PCR to enhance forensic DNA analysis and diagnostic PCR, providing an alternative to laborious sample preparation protocols.

  • 8.
    Libiseller, Claudia
    et al.
    Linköping University, Department of Mathematics, Statistics. Linköping University, The Institute of Technology.
    Nordgaard, Anders
    Linköping University, Department of Mathematics, Statistics. Linköping University, The Institute of Technology.
    Variance reduction for trend analysis of hydrochemical data from brackish waters2003Report (Other academic)
    Abstract [en]

    We propose one parametric and one non-parametric method for detection of monotone trends in nutrient concentrations in brackish waters. Both methods take into account that temporal variation in the quality of such waters can be strongly influenced by mixing of salt and fresh water, thus salinity is used as a classification variable in the trend analysis. With the non-parametric approach, Mann-Kendall statistics are calculated for each salinity level, and the parametric method involves the use of bootstrap estimates of the trend slope in a time series regression model. In both cases, tests for each salinity level are combined in an overall trend test.

  • 9.
    Libiseller, Claudia
    et al.
    Linköping University, Department of Mathematics, Statistics . Linköping University, Faculty of Arts and Sciences.
    Nordgaard, Anders
    Linköping University, Department of Mathematics, Statistics . Linköping University, Faculty of Arts and Sciences.
    Variance Reduction for Trend Analysis of Hydrochemical Data in Brackish Waters2002In: Environmental Communication in the Information Society: Proceedings of the 16th Conference “Informatics for Environmental Protection” Sept. 25-27, 2002, Vienna, Austria / [ed] Pillmann W., Tochtermann K, Vienna: ISEP , 2002Conference paper (Refereed)
  • 10.
    Nordgaard, Anders
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    A resampling technique for estimating the power of non-parametric trend tests2004In: COMPSTAT 2004, Prague, Czech Republic, 2004Conference paper (Other academic)
    Abstract [en]

    The power of Mann-Kendall tests and other non-parametric trend tests is normally estimated by performing Monte-Carlo simulations in which artificial data are generated according to simple parametric models. Here we introduce a resampling technique for power assessments that can be fully automated and accommodate almost any variation incollected time series data. A rank regression model is employed to extract error terms representing irregular variation in data that have been gathered over several seasons and may contain a non-linear trend. Thereafter, an autoregressive bootstrap method is used to generate new time series of error terms for power simulations. These innovations are combined with trend and seasonal components from the fitted rank regression model, and the trend function can be resampled. We also describe a study of water quality data from two Swedish rivers to illustrate how our method can provide site- and variable-specific information about the power of the Hirsch and Slack test for monotonic trends. In particular, we show how our technique can clarify the impact of sampling frequency on the power of this type of trend test.

  • 11.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences. Polismyndigheten - Nationellt Forensiskt Centrum.
    Activity level and evaluative reports on forensic science evidence2013Conference paper (Other academic)
  • 12.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Challenges in forensic evidence evaluation2012Conference paper (Other academic)
    Abstract [en]

    Interpretation andevaluation of forensic evidence is in essence a matter of probabilistic reasoning.The absence of models and sufficient background databases designed specificallyfor each particular forensic case make it a challenge to pursue such reasoning.However, with a coherent framework it is possible to reason with subjectiveprobabilities (subjective in the sense that they depend on the expert’sexperience and general knowledge) without leaving the court with a statementthat is merely the expert’s personal opinion. Bayesian reasoning, through theuse of Bayes factors (or very often likelihood ratios) constitutes such aframework. Here we present how the use of an ordinal scale for the Bayes factorcan allay the fear of subjectivity, and also how it can ease the problem ofevaluating evidence when there are multiple explanations for the forensicfindings with different likelihoods.

  • 13.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Construction of a scale of conclusions and its use for all types of forensic evidence2011Conference paper (Other (popular science, discussion, etc.))
  • 14.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences. Swedish Police Author, National Forens Centre, SE-58194 Linkoping, Sweden.
    Editorial Material: Comment on Dismissal of the illusion of uncertainty on the assessment of a likelihood ratio by Taroni F., Bozza S., Biederman A. and Aitken C.(1) in LAW PROBABILITY and RISK, vol 15, issue 1, pp 17-222016In: Law, Probability and Risk, ISSN 1470-8396, E-ISSN 1470-840X, Vol. 15, no 1, 17-22 p.Article in journal (Other academic)
    Abstract [en]

    n/a

  • 15.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Hållbar utveckling - aktuella statistiska utmaningar och problem i arbetet med miljöfrågor och utvecklingsövervakning2008In: Statistisk metod & analys - Skarpsynt utredning genom träffsäker datainsamling, IQPC, Stockholm, Sweden, 2008Conference paper (Other (popular science, discussion, etc.))
  • 16.
    Nordgaard, Anders
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Impact of sampling frequencies on the power of nonparametric tests for water quality trends2003In: The Information Society and Enlargement of the European Union: 17th International Conference, Informatics for Environmental Protection, Cottbus 2003 / [ed] Gnauck A, Heinrich R, Marburg: Metropolis Verlag , 2003Conference paper (Refereed)
  • 17.
    Nordgaard, Anders
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Impact of sampling frequency on the power of nonparametric tests for water quality trends2003In: SPRUCE VI International conference, Lund, Sweden, 2003Conference paper (Other academic)
  • 18.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences. Polismyndigheten - Nationellt Forensiskt Centrum.
    Interpreting findings – evaluation and conclusions about what happened at the crime scene2014Conference paper (Other (popular science, discussion, etc.))
  • 19.
    Nordgaard, Anders
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Power of non-parametric trend tests -- a semi-parametric approach2003In: The 14th Annual Conference of The International Environmetrics Society (TIES), Johannesburg, South Africa, 2003Conference paper (Other academic)
  • 20.
    Nordgaard, Anders
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Quantifying experience in sample size determination for drug analysis2006In: Law, Probability and Risk, ISSN 1470-8396, E-ISSN 1470-840X, Vol. 4, no 4, 217-225 p.Article in journal (Refereed)
    Abstract [en]

     Forensic analysis of pills suspected to contain illegal drugs is a time-consuming process; therefore, only a small sample from a seizure can be investigated. Notwithstanding, for drugs like Ecstacy, experience of forensic analysts indicates that a seizure of tablets usually consists either wholly of illicit drugs or no illegal substances at all. Consequently, it should be possible to draw fairly accurate conclusions based on very small samples, if all pills in a sample are indeed analytically identical. The forensic experience is modelled using a beta prior distribution for the proportion of drug-containing tablets in a seizure, and the sample size is determined so that a certain confidence statement can be made about this proportion. The parameters of the beta prior must be set to correspond with the experience, and this paper suggests a method for estimating these parameter values from a database comprising analyst reports representing the experience. The technique is applied to proportions of Ecstacy pills, and the results show that a sample of five pills is enough to state with a high level of confidence that at least half the tablets in a presumed Ecstacy seizure are genuine.

  • 21.
    Nordgaard, Anders
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Resampling species-wise abundance data2006In: The 17th Annual Conference of The International Environmetrics Society (TIES), Kalmar, Sweden, 2006Conference paper (Other academic)
    Abstract [en]

     Monitoring the abundance of plant species in grasslands is time-consuming. Accordingly, sampling or inspection is usually sparse both in time and space. Typically, a grassland area is visited 1-2 times per decade, and each time 5-20 plots are inspected. For each plot (about one square meter) an inspection protocol, containing coverage data for up to 100 species, is established. The collected data can thus be characterized as high-dimensional and sparse. Moreover, it is not unusual that some of the monitored species are present in only a few of the investigated plots, i.e., the vectors of coverage data may contain numerous zeroes. The analysis of abundance data can be either multivariate or univariate. Canonical correlation analysis (CCA) and redundancy analysis (RDA) are widely used multivariate methods. Univariate analyses are usually applied to summary statistics, such as diversity indices or measures of evenness. In either case, the complexity of the data makes it difficult to use parametric models for inference about the whole grassland, and modest sample sizes prevents using asymptotic results. Due to this, nonparametric methods, such as permutation tests, are often used to assess trends in abundance data. However, the power of these tests may be low due to the small number of sampling occasions. Here, we propose a resampling technique that can be used to determine the distribution of arbitrary estimators or test statistics based on high-dimensional abundance data. The original idea of the bootstrap is to substitute the true (but unknown) cumulative distribution function (cdf) for an empirical cumulative distribution function (edf) calculated from a sample of observations. When the collected data can be regarded as a simple random sample, the bootstrap principle provides a convenient method to determine the distributions of a large number of moment-related statistics (e.g. Singh, 1981). Also, it has been demonstrated that regression or time series data can be resampled by first extracting residuals (or innovations) and then forming pseudo data by resampling these residuals (Wu, 1989; Kreiss & Franke, 1992). We propose high-dimensional abundance data be resampled by extracting residuals from a principal components factor analysis in which a small number of factors are retained. Furthermore, we handle point masses at zero (absent species) by using a truncated probit function to transform the original data prior to the principal components factor analysis, and to back-transform the pseudo data. The threshold and the number of factors retained are determined in such a way that the most important features of the resampled data are similar to those of the original observations in the most important resoe. In particular, the number of observed species should not differ too much. The latter is achieved by using a subsampling procedure, in which the number of zeros (i.e. non-observed species) in a subsample and in pseudo-data from that subsample are compared. Also, relative biases and coverage degrees of empirical confidence intervals are optimized. The performance of our procedure is illustrated by extensive simulations and a case study of temporal changes in Shannon entropy in a grassland in South West Sweden.

  • 22.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Resampling species-wise collected abundance data for flexible assessment of changes in biodiversity2007In: Bulletin of the ISI - Volume LXII: PROCEEDINGS, Lisboa, Portugal, 22-29 August 2007 / [ed] Gomes M.I.,Pinto Martins J.A.,Silva J.A., 2007, 1596-1603 p.Conference paper (Other academic)
  • 23.
    Nordgaard, Anders
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Sample-size Determination for Analysis of Ecstasy Pills2005In: The Sixth International Conference on Forensic Statistics, Tempe, AZ, USA, 2005Conference paper (Other academic)
    Abstract [en]

    By experience, a seizure of pills that is under suspicion to contain drugs will very likely either consist entirely of drug pills of the same kind or consist of pills with no drug-content at all. If this experience could be quantified, it is possible to reduce the number of pills that must be selected for analysis. Recent results show that a Bayesian approach to sample size determination expresses the problem in a more natural way from a forensic point of view, provided an informative prior can be defined. Also, the sample sizes can be further reduced in this framework compared with the more classical Hypergeometric approach. These results have been adopted by the European Network of Forensic Sciences Institutes (ENFSI) in the Guideline on Representative Drug Sampling, published by ENFSI Drug Working Group. In this text, as well as in other published results, it is suggested to use a beta-prior which should be highly left-skewed when assumptions of the above kind can be done. In this paper we show how a beta-prior can be calculated from a data-base of analysed Ecstasy pills. By dividing the data-base items into different sub-populations, it is possible to estimate the parameter in the prior that controls the left-skewness of the distribution.

  • 24.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences. Polismyndigheten - Nationellt Forensiskt Centrum.
    Värdering och rapportering av forensiska resultat vid SKL2014Conference paper (Other (popular science, discussion, etc.))
  • 25.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences. Polismyndigheten - Nationellt Forensiskt Centrum.
    Andersson, Kjell
    Polismyndigheten - Nationellt Forensiskt Centrum.
    Högberg, Carina
    Polismyndigheten - Nationellt Forensiskt Centrum.
    The Multivariate Kernel Likelihood Ratio Method Applied on Comparison of Amphetamine Seizures2014Conference paper (Other academic)
    Abstract [en]

    Comparison of seizures of amphetamine with respect to their origins of illicit manufacturing can be done by investigating the amphetamine impurity pattern. Such an impurity pattern is a result of an incomplete cleaning-up process – typical for illicit manufacturing – when producing the drug. The manufacturing process can be divided into three steps: (1) choosing a recipe for how to produce; (2) producing amphetamine oil; and finally (3) precipitating the amphetamine from the oil.

    The impurity pattern of the amphetamine will depend on the recipe itself, the conditions used for the synthesis, the precipitation process and the method of cleaning-up. The impurity profile is a chromatogram of around 150 different contaminants, of these contaminants 26 have been used by several European countries in police intelligence work to link manufacturers of illicit drugs [1]. However, the linkage methods used are investigative and not evaluative.   

    The issue addressed when two specific seizures are to be compared, and the results are going to be used in the court of law, is whether they originate from the same precipitation batch.  When this is true the impurity patterns of the two seizures are in general expected to be similar, at least for stable contaminants. This is a less expected result if the seizures originate from different batches.

    Interpretation of observed similarities and differences between the impurity patterns of two seizures is still to a large extent based on subjective judgements where in Sweden the experiences of two forensic experts are used. In this presentation we show how the so-called multivariate kernel likelihood ratio approach [2] can be used for this interpretation. From a designed experiment comprising several recipes, the variance components for a subset or for a lower-dimensional projection of all contaminants are estimated and likelihood ratios can then be easily calculated. A cross-validatory study shows high sensitivity as well as high specificity of the likelihood ratios.

  • 26.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Molecular genetics. Linköping University, The Institute of Technology.
    Drotz, Weine
    Statens Kriminaltekniska Laboratorium.
    Jaeger, Lars
    Statens Kriminaltekniska Laboratorium.
    Scale of conclusions for the value of evidence2012In: Law, Probability and Risk, ISSN 1470-8396, E-ISSN 1470-840X, Vol. 11, no 1, 1-24 p.Article in journal (Refereed)
    Abstract [en]

    Scales of conclusion in forensic interpretation play an important role in the interface between scientific work at a forensic laboratory and different bodies of the jurisdictional system of a country. Of particular importance is the use of a unified scale that allows interpretation of different kinds of evidence in one common framework. The logical approach to forensic interpretation comprises the use of the likelihood ratio as a measure of evidentiary strength. While fully understood by forensic scientists, the likelihood ratio may be hard to interpret for a person not trained in natural sciences or mathematics. Translation of likelihood ratios to an ordinal scale including verbal counterparts of the levels is therefore a necessary procedure for communicating evidence values to the police and in the courtroom. In this paper, we present a method to develop an ordinal scale for the value of evidence that can be applied to any type of forensic findings. The method is built on probabilistic reasoning about the interpretation of findings and the number of scale levels chosen is a compromise between a pragmatic limit and mathematically well-defined distances between levels. The application of the unified scale is illustrated by a number of case studies.

  • 27.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences. Polismyndigheten - Nationellt Forensiskt Centrum.
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Biology. Linköping University, Faculty of Science & Engineering.
    Hedell, Ronny
    Polismyndigheten - Nationellt Forensiskt Centrum.
    ’Blame the brother’-Assessment of forensic DNA evidence when alternative explanations have different likelihoods2011Conference paper (Other academic)
    Abstract [en]

    In a crime case where a suspect is assumed to be the donor of a recovered stain, forensic DNA evidence presented in terms of a likelihood ratio is a clear course as long as the set of alternative donors contains no close relative of the suspect, since the latter has a higher likelihood than has an individual unrelated to the suspect. The state-of-art today at several laboratories is to report the likelihood ratio but with a reservation stating its lack of validity if the stain originates from a close relative. Buckleton et al[†] derived a so-called extended likelihood ratio for reporting DNA evidence values when a full sibling is present in the set of potential alternative donors. This approach requires consideration of prior probabilities for each of the alternative donors to be the source of the stain and may therefore be problematic to apply in practice. Here we present an alternative way of using prior probabilities in the extended likelihood ratio when the latter is reported on an ordinal scale of conclusions. Our example show that for a 12 STR-marker profile using the extended likelihood ratio approach would not imply a change in the level reported compared to the ordinary likelihood ratio approach, unless the close relative has a very high prior probability of being the donor compared to an unrelated individual.

    [†] Buckleton JS, Triggs CM, Champod C., Science & Justice 46: 69-78.

     

  • 28.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Molecular genetics .
    Jaeger, Lars
    Swedish National Laboratory of Forensic Sciences, Linköping, Sweden.
    Drotz, Weine
    Swedish National Laboratory of Forensic Sciences, Linköping, Sweden.
    Ordinal scales of conclusions for the value of evidence2009In: 5th European Academy of Forensic Science Conference, Glasgow, UK, 2009Conference paper (Other academic)
  • 29.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Du, Yang
    Change-point detection in environmental time series –A Bayesian approach2010In: The 21th Annual Conference of The International Environmetrics Society (TIES), Margarita Island, Venezuela, 2010Conference paper (Other academic)
  • 30.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences. Polismyndigheten - Nationellt Forensiskt Centrum.
    Emanuelson, Anna
    Statens Kriminalteksniska Laboratorium.
    Mannerskog, Susanne
    Polismyndigheten - Nationellt Forensiskt Centrum.
    Svensson, Ulf
    Polismyndigheten - Natinellt Forensiskt Centrum.
    Ekberg, Kajsa
    Polismyndigheten - Nationellt Forensiskt Centrum.
    Jonasson, Lennart
    Polismyndigheten - Nationellt Forensiskt Centrum.
    Lövby, Märtha
    Polismyndigheten - Nationellt Forensiskt Centrum.
    Brorsson Läthén, Klas
    Polismyndigheten - Nationellt Forensiskt Centrum.
    Leitet, Elisabet
    Polismyndigheten - Nationellt Forensiskt Centrum.
    Indirect Evaluation by Simulation of a Bayesian Network2014Conference paper (Other academic)
    Abstract [en]

    Evidence evaluation when addressing source level propositions is usually done by comparing a piece of recovered material from (specimens of) control material. When the control material source is not available for taking specimens or for investigating it in its entirety, we must stick to photographs or video take-ups for making comparisons. An example is the comparison of class characteristics between a recovered footwear print and a picture of a seized shoe, where the evaluation is occasionally made that way. However, this way of pursuing the investigation is due to needs of quick answers, when there is no or little time to send in the entire footwear for the comparison. Moreover, the pictures taken of the sole of the seized footwear are taken by the police under controlled conditions and with high quality equipment.

    When the suspected source is captured on a lower quality video take-up and the recovered material consists of fragments from the original body of material – for instance fire debris – the comparison with the control material source is naturally more difficult. In this paper we present a case where the question is whether recovered fire debris originate from a piece of garment captured on a CCTV take-up. We show how a likelihood ratio for the two propositions can be indirectly obtained from a classification of the source of the fire debris, by using a Bayesian network model. Results from fire debris analysis as well as the results from image comparisons can be evaluated against propositions of class and the updating of the class node for fire debris propagates back to the propositions for source.

    Feeding the network with uniform priors for the class nodes we show how simulation can be used to obtain the correct level of the likelihood ratio for further reporting.

  • 31.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Hedberg, Karin
    Statens Kriminaltekniska Laboratorium.
    Widén, Christina
    Statens Kriminaltekniska Laboratorium.
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Molecular genetics. Linköping University, The Institute of Technology.
    Comments on ‘‘The database search problem’’ with respect to a recent publication in Forensic Science International: Letter to the Editor2012In: Forensic Science International, ISSN 0379-0738, E-ISSN 1872-6283, Vol. 217, no 1-3, e32-e33 p.Article in journal (Refereed)
  • 32.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Hedell, Ronny
    Statens Kriminaltekniska Laboratorium, Linköping.
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Molecular genetics. Linköping University, The Institute of Technology.
    Assessment of forensic findings when alternative explanations have different likelihoods—“Blame-the-brother”-syndrome2012In: Science & justice, ISSN 1355-0306, E-ISSN 1876-4452, Vol. 52, no 4, 226-236 p.Article in journal (Refereed)
    Abstract [en]

    Assessment of forensic findings with likelihood ratios is for several cases straightforward, but there are a number of situations where contemplation of the alternative explanation to the evidence needs consideration, in particular when it comes to the reporting of the evidentiary strength. The likelihood ratio approach cannot be directly applied to cases where the proposition alternative to the forwarded one is a set of multiple propositions with different likelihoods and different prior probabilities. Here we present a general framework based on the Bayes' factor as the quantitative measure of evidentiary strength from which it can be deduced whether the direct application of a likelihood ratio is reasonable or not. The framework is applied on DNA evidence in forms of an extension to previously published work. With the help of a scale of conclusions we provide a solution to the problem of communicating to the court the evidentiary strength of a DNA match when a close relative to the suspect has a non-negligible prior probability of being the source of the DNA.

  • 33.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Hedman, Johannes
    Department of Applied Microbiology, Lund University, Sweden .
    Ansell, Ricky
    Linköping University, Department of Physics, Chemistry and Biology, Molecular genetics .
    The forensic DNA profile index - a tool for comparison of electropherograms2010In: English Speaking Working Group (ESWG), International Society of Forensic Genetics (ISFG) Stockholm, Sweden, 2010Conference paper (Other academic)
    Abstract [en]

    Background

    Assessment of DNA profile quality is vital in forensic DNA analysis, both in order to determine the evidentiary value of DNA results and to compare the performances of different DNA analysis protocols. Generally the quality assessment is performed through manual examination of the DNA profiles based on empirical knowledge, or by comparing the intensities (allelic peak heights) of the capillary electrophoresis electropherograms.

    We recently1 developed a ranking index for unbiased and quantitative quality assessment of forensic DNA profiles, the forensic DNA profile index (FI).

     

    Core of presentation

    FI uses electropherogram data to combine the intensities of the allelic peaks with the balances within and between loci, using Principal Components Analysis. Here we present the construction of FI. We explain the mathematical and statistical methodologies used and present details about the applied data reduction method. Thereby we show how to adapt the ranking index for any STR-based forensic DNA typing system through validation against a manual grading scale and calibration against a specific set of DNA profiles.

     

    1 Hedman J, Nordgaard A, Rasmusson B, Ansell R,  Rådström P (2009), Improved forensic DNA analysis through the use of alternative DNA polymerases and statistical modelling of DNA profiles, Biotechniques 47, 351-358.

  • 34.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Höglund, Tobias
    Statens Kriminaltekniska Laboratorium.
    Assessment of Approximate Likelihood Ratios from Continuous Distributions: A Case Study of Digital Camera Identification2011In: Journal of Forensic Sciences, ISSN 0022-1198, E-ISSN 1556-4029, Vol. 56, no 2, 390-402 p.Article in journal (Refereed)
    Abstract [en]

    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.

  • 35.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Höglund, Tobias
    Swedish National Laboratory of Forensic Sciences.
    The use of likelihood ratios in digital camera identification2008In: The Seventh International Conference on Forensic Inference and Statistics, Lausanne, CH, 2008Conference paper (Other academic)
  • 36.
    Nordgaard, Anders
    et al.
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Libiseller, Claudia
    Linköping University, Faculty of Arts and Sciences. Linköping University, Department of Mathematics, Statistics .
    Variance reduction for trend analysis2002In: NORDSTAT 2002, Stockholm, Sweden, 2002Conference paper (Other academic)
    Abstract [en]

    The concentrations of nutrients and other substances in a water body can be strongly influenced by random fluctuations in the mixing of waters of different origin. Hence, the water quality at given site can exhibit a large temporal variation that makes it difficult to extract anthropogenic signals from collected data. In this paper, we examine how the human impact on nutrient concentrations in such water bodies can be clarified by replacing conventional time series or geostatistical approaches by trend detection techniques in which we analyse the variation in nutrient concentrations with salinity and time. The general principles for the trend detection are illustrated with data from the Baltic Sea. The statistical significance of temporal changes in nutrient concentrations can be assessed by using parametric and nonparametric trend tests. In the recent past a nonparametric trend test with correction for covariates was proposed (Libiseller and Grimvall, 2002). This test, however, can best be applied if trends are monotone in time, which is not necessarily fulfilled for the original data. We therefore suggest that an overall trend test is computed as the weighted sum of trend test statistics computed for different salinity levels. By this means we receive a rather homogeneous time series in each subset, which considerably improves the power of the trend test. In the parametric approach we suggest a regression model, with Total Phosphorus concentration as the dependent variable and time (months) as the explaining variable. The residuals from this model output are most likely non-independent and non-normally distributed, and we will therefore apply bootstrap assessment of the estimated parameters.

  • 37.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Rasmusson, Birgitta
    Statens Kriminaltekniska Laboratorium, Linköping.
    The likelihood ratio as value of evidence—more than a question of numbers2012In: Law, Probability and Risk, ISSN 1470-8396, E-ISSN 1470-840X, Vol. 11, 303-315 p.Article in journal (Refereed)
    Abstract [en]

    The ability of the experienced forensic scientist to evaluate his or her results given the circumstances and propositions in a particular case and present this to the court in a clear and concise way is very important for the legal process. Court officials can neither be expected to be able to interpret scientific data, nor is it their task to do so (in our opinion). The duty of the court is rather to perform the ultimate evidence evaluation of all the information in the case combined, including police reports, statements from suspects and victims, witness reports forensic expert statements, etc. Without the aid of the forensic expert, valuable forensic results may be overlooked or misinterpreted in this process. The scientific framework for forensic interpretation stems from Bayesian theory. The resulting likelihood ratio, which may be expressed using a verbal or a numerical scale, compares how frequent are the obtained results given that one of the propositions holds with how frequent  they are given that the other proposition holds. A common misunderstanding is that this approach must be restricted to forensic areas such as DNA evidence where extensive background information is present in the form of comprehensive databases. In this article we argue that the approach with likelihood ratios is equally applicable in areas where the results rely on scientific background data combined with the knowledge and experience of the forensic scientist. In such forensic areas the scale of the likelihood ratio may be rougher compared to a DNA case, but the information that is conveyed by the likelihood ratio may     nevertheless be highly valuable for the court.

  • 38.
    Nordgaard, Anders
    et al.
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Wahlin, Karl
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Grimvall, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
    Uncertainty in water quality data and its implications for trend detection2007In: Bulletin of the ISI, Vol. LXII: Proceedings, Lisboa, Portugal, 22-29 AUgust 2007 / [ed] Gomes M.I., Pinto Martins J.A., Silva J.A., 2007, 2597-2600 p.Conference paper (Other academic)
  • 39.
    Sydsjö, Gunilla
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, Department of Gynaecology and Obstetrics in Linköping.
    Kvist, Ulrik
    Karolinska University Hospital, Sweden; Huddinge University Hospital, Sweden.
    Bladh, Marie
    Linköping University, Department of Clinical and Experimental Medicine, Division of Clinical Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, Department of Gynaecology and Obstetrics in Linköping. Linköping University, Faculty of Medicine and Health Sciences.
    Nordgaard, Anders
    Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences. Swedish Police Authority, National Forensic Centre, Linkoping, Sweden.
    The optimal number of offspring per gamete donor2015In: Acta Obstetricia et Gynecologica Scandinavica, ISSN 0001-6349, E-ISSN 1600-0412, Vol. 94, no 9, 1022-1026 p.Article in journal (Refereed)
    Abstract [en]

    Our aim was to create a mathematical basis to calculate the risks for unintended matings of consanguineous half-siblings from a donor in a society with approximately 10 million inhabitants. The Curie-Cohen model for calculation of the risk for consanguineous mating was used. When the number of offspring per donor is limited to 10, then the model gives a yearly risk for consanguineous matings below 1%. Thus 10 offspring gives a risk for consanguineous matings of 0.9% per year, or approximately once in every 100years. The risk increases exponentially: with 15 offspring it exceeds 2% and with 25 it reaches up above 5%.

1 - 39 of 39
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