Skip to main content Accessibility help
×
Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-26T14:00:04.259Z Has data issue: false hasContentIssue false

References

Published online by Cambridge University Press:  09 April 2021

Ronald Meester
Affiliation:
Vrije Universiteit, Amsterdam
Klaas Slooten
Affiliation:
Vrije Universiteit, Amsterdam
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Probability and Forensic Evidence
Theory, Philosophy, and Applications
, pp. 431 - 439
Publisher: Cambridge University Press
Print publication year: 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Aitken, C. and Taroni, F.. Statistics and the Evaluation of Evidence for Forensic Scientists. Wiley, 2004.CrossRefGoogle Scholar
[2] Aitkin, M.. Statistical Inference: An Integrated Bayesian/Likelihood Approach. Chapman and Hall, 2010.CrossRefGoogle Scholar
[3] Anderson, T. J., Schum, D. A., and Twining, W. L.. Analysis of Evidence. Cambridge Universiy Press, 2005.CrossRefGoogle Scholar
[4] Ayres, I. and Nalebuff, B.. The rule of probabilities: A practical approach for applying Bayes’ rule to the analysis of DNA evidence. Stanford Law Review, 67:14471503, 2015.Google Scholar
[5] Balding, D. J.. Weight-of-evidence for Forensic DNA Profiles. Wiley, 2005.Google Scholar
[6] Balding, D. J.. The DNA database controversy. Biometrics, 58:241244, 2002.Google Scholar
[7] Balding, D. J.. Evaluation of mixed-source, low-template DNA profiles in forensic science. Proceedings of the National Academy of Sciences of the United States of America, 110(30):1224112246, 2013.Google Scholar
[8] Balding, D. J. and Donnelly, P.. Inference in Forensic Identification. Journal of the Royal Statistical Society, Series A, 158(1):2153, 1995.Google Scholar
[9] Balding, D. J. and Donnelly, P.. Inferring identity from DNA profile evidence. Proceedings of the National Academy of Sciences USA, 92:1174111745, 1995.Google Scholar
[10] Balding, D. J. and Donnelly, P.. Evaluating DNA profile evidence when the suspect is found through a database search. Journal of Forensic Sciences, 41:603607, 1996.Google Scholar
[11] Balding, D. J., Krawczak, M., Buckleton, J. S., and Curran, J. M.. Decision-making in familial database searching: KI alone or not alone? Forensic Science International: Genetics, 7(1):5254, 2013.Google Scholar
[12] Balding, D.J. and Nichols, R.A.. DNA profile match probability calculation: how to allow for population stratification, relatedness, database selection and single bands. Forensic Science International, 64:125140, 1994.Google Scholar
[13] Balding, D. J. and Nichols, R. A.. A method for quantifying differentiation between populations at multi-allelic loci and its implications for investigating identity and paternity. Genetica, 96:312, 1995.Google Scholar
[14] Beecham, G. W. and Weir, B. S.. Confidence interval of the likelihood ratio associated with mixed stain DNA evidence. Journal of Forensic Science, 56:S166–S171, 2011.Google Scholar
[15] Bello, M. D.. Trail by statistics: Is a high probability of guilt enough to convict? Mind, 128:10451084, 2019.Google Scholar
[16] Benschop, C. C. G., Nijveld, A., Duijs, F. E., and T. Sijen. An assessment of the performance of the probabilistic genotyping software EuroForMix: Trends in likelihood ratios and analysis of Type I & II errors. Forensic Science International: Genetics, 42:31–38, 2019.Google ScholarPubMed
[17] Berger, C. E. H. and Slooten, K.. The LR does not exist. Science and Justice, 56:388391, 2016.CrossRefGoogle Scholar
[18] Berger, C. E. H., Vergeer, P., and Buckleton, J. S.. A more straightforward derivation of the LR for a database search. Forensic Science International: Genetics, 14:156160, 2015.CrossRefGoogle ScholarPubMed
[19] Biedermann, A., Bozza, S., Taroni, F., and Aitken, C.. The consequences of understanding expert probability reporting as a decision. Science and Justice, 57:8085, 2016.Google Scholar
[20] Biedermann, A., Bozza, S., Taroni, F., and Aitken, C.. Reframing the debate: A question of probability, not of likelihood ratio. Science and Justice, 56:392396, 2016.Google Scholar
[21] Biedermann, A., Gittelson, S., and Taroni, F.. Recent misconceptions about the “database search problem”: A probabilistic analysis using Bayesian networks. Forensic Science International, 212:5160, 2011.CrossRefGoogle ScholarPubMed
[22] Bille, T., Weitz, S., Buckleton, J. S., and Bright, J.-A.. Interpreting a major component from a mixed DNA profile with an unknown number of minor contributors. Forensic Science International: Genetics, 40:150159, 2019.Google Scholar
[23] Bleka, Ø., Benschop, C. G., Storvik, G., and Gill, P.. A comparative study of qualitative and quantitative models used to interpret complex STR DNA profiles. Forensic Science International: Genetics, 25:8596, 2016.Google Scholar
[24] Bleka, Ø., Storvik, G., and Gill, P.. EuroForMix: An open source software based on a continuous model to evaluate STR DNA profiles from a mixture of contributors with artefacts. Forensic Science International: Genetics, 21:3544, 2016.CrossRefGoogle ScholarPubMed
[25] Bolck, A., Ni, H., and Lopatka, M.. Evaluating score- and feature-based likelihood ratio models for multivariate continuous data: Applied to forensic MDMA comparison. Law, Probability and Risk, 14:243266, 2015.Google Scholar
[26] Bosma, W., Dalm, S., Van Dijk, E., Harchaoui, R. E., E. Rijgersberg, H. T. Tops, A. Veenstra, and Ypma R. Establishing phone-pair co-usage by comparing mobility patterns. Science and Justice, 2019.CrossRefGoogle Scholar
[27] Briggs, W.. Uncertainty, the Soul of Modeling, Probability and Statistics. Springer, 2016.Google Scholar
[28] Van Den Brink, I.. Belief functies: theorie en een toepassing in een forensische context. Bachelor Thesis VU Amsterdam, 2017.Google Scholar
[29] Brümmer, N. and de Preez, J.. Application-independent evaluation of speaker detection. Computer Speech and Language, 20(2-3):230275, 2006.CrossRefGoogle Scholar
[30] Buckleton, J., C. M. Triggs, and S. J. Walsh (eds.). Forensic DNA Evidence Interpretation. CRC Press, 2005.Google Scholar
[31] Buckleton, J. S., Bright, J.-A., Cheng, K., Kelly, H., and Taylor, D.. The effect of varying the number of contributors in the prosecution and alternate propositions. Forensic Science International: Genetics, 38:225231, 2019.Google Scholar
[32] Butler, J.. Advanced Topics in Forensic DNA Typing: Methodology. Elsevier, 2012.Google Scholar
[33] Gomez Case. No. 99CF0391 Tr. Trans. (Cal. Superior Ct. Orange Cty.), 2002.Google Scholar
[34] Chung, Y.-K., Hu, Y.-Q., and Fung, W. K.. Familial database search on two-person mixture. Computational Statistics and Data Analysis, 54:20462051, 2010.Google Scholar
[35] Cohen, L. J.. The Probable and the Provable. Clarendon Press, 1977.Google Scholar
[36] Cole, R.. Forensics without uniqueness, conclusions without individualization: The new epistemology of forensic identification. Law, Probability and Risk, 8:233255, 2009.Google Scholar
[37] Collins, A. and Morton, N. E.. Likelihood ratios for DNA identification. Proceedings of the National Academy of Sciences USA, 91:60076011, 1994.Google Scholar
[3838] Cooke, R.. Experts in Uncertainty – Opinion and Subjective Probability in Science. Oxford University Press, 1991.CrossRefGoogle Scholar
[39] Cowell, R. G.. Computation of marginal distributions of peak-heights in electro-pherogramsfor analysing single source and mixture STR DNA samples. Forensic Science International: Genetics, 35:164168, 2018.Google Scholar
[40] Cowell, R. G.. A unifying framework for the modelling and analysis of STR DNA samples arising in forensic casework. Arxiv.org/abs/1802.09863, 2018.Google Scholar
[41] Cowell, R. G., Dawid, A. P., Lauritzen, S. L., and Spiegelhalter, D. J.. Probabilistic Networks and Expert Systems. Springer, 1999.Google Scholar
[42] Cowell, R. G., Graversen, T., Lauritzen, S. L., and Mortera, J.. Analysis of forensic DNA mixtures with artefacts. Journal of the Royal Statistical Society Series C (with discussion), 64(1):1–48, 2014.Google Scholar
[43] Cowell, R. G., Graversen, T., Lauritzen, S. L., and Mortera, J.. Analysis of forensic DNA mixtures with artefacts. Journal of the Royal Statistical Society. Series C: Applied Statistics, 64(1):148, 2015.Google Scholar
[44] Cowen, S. and Thomson, J.. A likelihood ratio approach to familial searching of large DNA databases. Forensic Science International: Genetics Supplementary Series, 1:643645, 2008.Google Scholar
[45] Curran, J. M.. Statistics in forensic science. WIREs Computational Statistics, 1:141156, 2009.Google Scholar
[46] Curran, J. M. and Buckleton, J. S.. Effectiveness of familial searches. Science and Justice, 84:164167, 2008.Google Scholar
[47] Cuzzolin, F.. Visions of a Generalized Probability Theory. Lambert Academic Publishing, 2014.Google Scholar
[48] Cuzzolin, F.. The Geometry of Uncertainty. Springer, 2016.Google Scholar
[49] Dahlman, C.. The felony fallacy. Law, Probability and Risk, 14:229241, 2015.Google Scholar
[50] Dahlman, C.. De-biasing legal fact-finders with Bayesian thinking. Topics in Cognitive Science, 2019.Google Scholar
[51] Dawid, A. P.. Comment on Stockmarr’s “likelihood ratios for evaluating DNA evidence when the suspect is found through a database search.Biometrics, 57:976980, 2001.Google Scholar
[52] Dawid, A. P.. Beware of the DAG! JMLR: Workshop and Conference Proceedings, (6), 2008.Google Scholar
[53] Dawid, A. P.. Probability and proof. www.cambridge.org, 2008.Google Scholar
[54] Dawid, A. P. and Mortera, J.. Forensic identification with imperfect evidence. Biometrika, 85(4):835849, 1998.CrossRefGoogle Scholar
[55] de Finetti, B.. Theory of Probability. John Wiley & Sons, 1975.Google Scholar
[56] DeKoeijer, J.. Combining evidence in complex cases – a comprehensive approach to interdisciplinary casework. Science and Justice, 2019.Google Scholar
[57] Donnely, P. and Friedman, R. D.. DNA database searches and the legal consumption of scientific evidence. Michigan Law Review, 97:931984, 1999.Google Scholar
[58] Dørum, G., Bleka, Ø., Gill, P., Haned, H., and Egeland, T.. Exact computation of the distribution of likelihood ratios with forensic applications. Forensic Science International: Genetics, 9:93101, 2014.Google Scholar
[59] Dubois, D. and Prade, H.. Evidence, knowledge and belief functions. Journal of Approximate Reasoning, 6:295319, 1992.Google Scholar
[60] ENFSI Guideline for Evaluative Reporting in Forensic Science. Available online: http://enfsi.eu/wp-content/uploads/2016/09/m1 guideline .pdf. ENFSI, 2015.Google Scholar
[61] Evett, I. W., Berger, C. E. H., Buckleton, J. S., Champod, C., and Jackson, G.. Finding the way forward for forensic science in the US – a commentary on the PCAST report. Forensic Science International, 2017.Google Scholar
[62] Evett, I. W., Foreman, L. A., and Weir, B. S.. Letter to the Editor. Biometrics, 56:12741275, 2000.Google ScholarPubMed
[63] Evett, I. W. and Weir, B. S.. Interpreting DNA Evidence: Statistical Genetics for Forensic Scientists. Sinauer Associates, Sunderland, 1998.Google Scholar
[64] Fagin, R. and Halpern, J. Y.. Uncertainty, belief and probability. Computational Intelligence, 6:160173, 1989.Google Scholar
[65] Fenton, N. and Neil, M.. The Jury Fallacy and the use of Bayesian nets to simplify probabilistic legal arguments. Mathematics Today (Bulletin of the IMA), 36, 2000.Google Scholar
[66] Fenton, N., Neil, M., Lagnado, D., Marsh, W., and Yet, B.. How to model mutually exclusive events based on independent causal pathways in Bayesian network models. Knowledge-Based Systems, 113:3950, 2016.Google Scholar
[67] Fenton, N., Neil, M., Yet, B., and Lagnado, D.. Analyzing the Simonshaven case using Bayesian networks. Topics in Cognitive Science, 2019.Google Scholar
[68] Fisher, R. A.. Statistical Methods for Research Workers. Oliver and Boyd, 1925.Google Scholar
[69] Ge, J., Chakraborty, R., Eisenberg, A., and Budowle, B.. Comparisons of familial DNA database searching strategies. Journal of Forensic Science, 56:14481456, 2011.Google Scholar
[70] Gill, P. and Haned, H.. A new methodological framework to interpret complex DNA profiles using likelihood ratios. Forensic Science International: Genetics, 7:251263, 2013.Google Scholar
[71] Gill, P., Hicks, T., Butler, J. M., Connolly, E., Gusmao, L., Kokshoorn, B., Morling, N., Van Oorschot, R. A. H. W. Parson, M. Prinz, P. M. Schneider, T. Sijen, , and Taylor, D.. DNA commission of the International society of forensic genetics: Assessing the value of forensic biological evidence – Guidelines highlighting the importance of propositions. Forensic Science International: Genetics, 36(36):189202, 2018.Google Scholar
[72] Good, I. J.. Studies in the history of probability and statistics. XXXVII A.M. Turing’s statistical work in World War II. Biometrika, 66(2):393–396, 1979.Google Scholar
[73] Goodman, S.. A Dirty Dozen: Twelve P-Value Misconceptions. Seminars in Hematology, 45:135140, 2008.Google Scholar
[74] Hacking, I.. Logic of Statistical Inference. Cambridge University Press, 1965.Google Scholar
[75] Hall, M.. Combinatorial Theory. Wiley, 1998.Google Scholar
[76] Haned, H., Pène, L., Lobry, J. R., Dufour, A. B., and Pontier, D.. Estimating the number of contributors to forensic DNA mixtures: Does maximum likelihood perform better than maximum allele count? Journal of Forensic Sciences, 56(1):2328, 2011.Google Scholar
[77] Haned, H., Slooten, K., and Gill, P.. Exploratory data analysis for the interpretation of low template DNA mixtures. Forensic Science International: Genetics, 6(6):762774, 2012.Google Scholar
[78] Haned, H., Dørum, G., Egeland, T., and Gill, P.. On the meaning of the likelihood ratio: Is a large number always an indication of strength of evidence? Forensic Science International: Genetics Supplement Series, 4(1):e176–e177, 2013.Google Scholar
[79] Hicks, T., Taroni, F., Curran, J., Buckleton, J., Castella, V., and Ribaux, O.. Use of DNA profiles for investigation using a simulated national DNA database: Part II. Statistical and ethical considerations on familial searching. Forensic Science International: Genetics, 4(5):316322, 2010.Google Scholar
[80] Van Den Hout, A. and Alberink, I.. Posterior distributions for likelihood ratios in forensic science. Science and Justice, 56:397401, 2016.Google Scholar
[81] Hubbard, R. and Lindsay, R. M.. Why P-values are not a useful measure of evidence in statistical significance testing. Theory and Psychology, 18:6988, 2008.Google Scholar
[82] Hummel, K.. On the theory and practice of Essen-Möller’s W value and Gürtler’s paternity index (PI). Forensic Science International, 1984.Google Scholar
[83] Kerkvliet, T. and Meester, R.. Assessing forensic evidence by computing belief functions. Law, Probability and Risk, 15:127153, 2016.Google Scholar
[84] Kerkvliet, T. and Meester, R.. A behavioral interpretation of belief functions. Journal of Theoretical Probability, 31:21122128, 2017.Google Scholar
[85] Kerkvliet, T. and Meester, R.. Finding persons with special features using belief functions. Preprint, 2019.Google Scholar
[86] Kerkvliet, T. and Meester, R.. A new look at conditional belief functions. Statistica Neerlandica, pages 1–18, 2019.Google Scholar
[87] Kim, J., Mammo, D., Siegel, M. B., and Katsanis, S. H.. Policy implications for familial searching. Investigative Genetics, 2:22, 2011.Google Scholar
[88] Koehler, J. J.. One in millions, billions, and trillions: Lessons from People v. Collins (1968) for People v. Simpson. Journal of Legal Education, 47:214–223, 1997.Google Scholar
[89] Van Koppen, P. J.. De Tengelhamer en het Schedeldak. Nederlands Juristenblad, 21:14441452, 2017.Google Scholar
[90] Kruijver, M.. Characterizing the genetic structure of a forensic DNA database using a latent variable apporach. Forensic Science International: Genetics, 23:130149, 2016.Google Scholar
[91] Kruijver, M., Meester, R., and Slooten, K.. P-values should not be used for evaluating the strength of DNA evidence. Forensic Science International: Genetics, 16: 226231, 2015.Google Scholar
[92] Kruijver, M. V., Meester, R., and Slooten, K.. Optimal strategies for familial searching. Forensic Science International: Genetics, 13:90103, 2014.Google Scholar
[93] Lauritzen, S. L., Dawid, A. P., Larsen, B. N., and Leimer, H. G.. Independence properties of directed Markov fields. Networks, 20:491505, 1990.Google Scholar
[94] Lindley, D.. Understanding Uncertainty. John Wiley & Sons, 2014.Google Scholar
[95] Lucy, D.. Introduction to Statistics for Forensic Scientists. Wiley, 2005.Google Scholar
[96] Lucy, D. and Aitken, C.. A review of role of roster data and evidence of attendance in cases of suspected excess death in a medical context. Law, Probability and Risk, 1:141160, 2002.Google Scholar
[97] Maguire, C. N., McCallum, L. A., Storey, C., and Whitaker, J. P.. Familial searching: A specialist forensic DNA profiling service utilising the National DNA Database to identify unknown offenders via their relatives – the UK experience. Forensic Science International: Genetics, 8:19, 2014.Google Scholar
[98] Manabe, S., Morimoto, C., Hamano, Y., Fujimoto, S., and Tamaki, K.. Development and validation of open-source software for DNA mixture interpretation based on a quantitative continuous model. PLoS ONE, 12:118, 2017.Google Scholar
[99] Martire, K. A., Edmond, G., Navarro, D. N., and Newell, B. R.. On the likelihood of “encapsulating all uncertainty.Science and Justice, 57:7679, 2016.Google Scholar
[100] Meester, R.. Classical probabilities and belief functions in legal cases. Law, Probability and Risk, 2020.Google Scholar
[101] Meester, R., Collins, M., Gill, R., and Van Lambalgen, M.. On the (ab)use of statistics in the legal case against the nurse Lucia de B. Law, Probability and Risk, 5:233250, 2007.Google Scholar
[102] Meester, R. and Sjerps, M.. The evidential value in the DNA database search controversy and the two-stain problem. Biometrics, 59:727732, 2003.Google Scholar
[103] Meester, R. and Sjerps, M.. Why the effect of prior odds should accompany the likelihood ratio when reporting DNA evidence. Law, Probability and Risk, 3:5162, 2004.Google Scholar
[104] Meester, R. and Slooten, K.. DNA database matches: A p versus np problem. Forensic Science Internatonal: Genetics, 46, 2020.Google Scholar
[105] Meuwly, D., Ramos, D., and Haraksim, R.. A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation. Forensic Science International, 276: 142153, 2017.Google Scholar
[106] Miller, G.. Familial DNA testing scores a win in serial killer case. Science, 329:262, 2010.Google Scholar
[107] Mitchell, A., L. Ostojic, F. Lucero, M. Prinz, and T. Caragine. Using simulation to improve understanding of likelihood ratio results. Proceedings of the 66th Annual Scientific Meeting of the American Academy of Forensic Sciences, 2014.Google Scholar
[108] Morrison, G. S.. Special issue on measuring and reporing the precision of forensic likelihood ratios: Introduction to the debate. Science and Justice, 56:371373, 2016.Google Scholar
[109] Morrison, G. S., Balding, D. H., Taylor, D. J., Dawid, P., Aitken, C., Gittelson, S., Zadora, G., Robertson, B., Willis, S. M., Pope, S., Neil, M., Martire, K. A., Hepler, A., Gill, R. D., Jamieson, A., De Zoete, J. R. B. Ostrum, , and Caliebe, A.. A comment on the PCAST report: Skip the “match”/”non-match” stage. Forensic Science International, 272:e7–e9, 2017.Google Scholar
[110] Myers, S., Tinken, M. D., Piucci, M. L., Sims, G. A., Greenwald, M. A., Weigand, J. J., Konzak, K. C., and Buoncristiani, M. R.. Searching for first-degree familial relationships in California’s offender DNA database: Validation of a likelihood ratio-based approach. Forensic Science International: Genetics, 5(5):493500, 2011.Google Scholar
[111] Nance, D. A.. Belief functions and burdens of proof. Law, Probability and Risk, 18:5376, 2018.Google Scholar
[112] Neil, M., Fenton, N., Lagnado, D., and Gill, R.. Modelling competing legal arguments using Bayesian model comparison and averaging. Artificial Intelligence and Law, 27, 2019.Google Scholar
[113] Nesson, C. R.. Reasonable doubt and permissive inferences: The value of complexity. Harvard Law Review, 92:11871225, 1979.Google Scholar
[114] Neyman, J.. First Course in Probability and Statistics. Holt, 1950.Google Scholar
[115] Nieuwbeerta, P. and Leistra, G.. Dodelijk gewels: moord en doodslag in Nederland. Amsterdam: Balans, 2007.Google Scholar
[116] Nordgaard, A. and Rasmusson, B.. The likelihood ratio as value of evidence – more than a question of numbers. Law, Probability and Risk, 11:303315, 2012.Google Scholar
[117] Nunn, G. A.. The incompatibility of due process and naked statistical evidence. Vanderbilt Law Review, 68:14071433, 2015.Google Scholar
[118] PCAST report: Forensic Science in the Criminal Courts: Ensuring Scientific Validity of Feature-Comparison Methods. Available online: www.justice.gov/archives/ncfs/page/file/933476/download.PCAST, 2016.Google Scholar
[119] Pearl, J. and Mackenzie, D.. The Book of Why: The New Science of Cause and Effect. Basic Books, 2018.Google Scholar
[120] Perlin, M. W.. Genotype Likelihood Ratio Distributions and Random Match Probability: Generalization, Calculation and Application. Cybergenetics report (online), July 2017.Google Scholar
[121] Perlin, M. W., Legler, M. M., Spencer, C. E., Smith, J. L., Allan, W. P., Belrose, J. L., and Duceman, B. W.. Validating true allele DNA mixture interpretation. Journal of Forensic Sciences, 56(6):14301447, 2011.Google Scholar
[122] Poincaré, J.. Science and Hypothesis. The Walter Scott Publishing Co., 1905.Google Scholar
[123] Puch-Solis, R., Rodgers, L., Mazumder, A., Pope, S., Evett, I., Curran, J., and Balding, D.. Evaluating forensic DNA profiles using peak heights, allowing for multiple donors, allelic dropout and stutters. Forensic Science International: Genetics, 7:555563, 2013.Google Scholar
[124] National Research Council. DNA Technology in Forensic Science. National Academy Press, 1992.Google Scholar
[125] National Research Council. The Evaluation of Forensic DNA Evidence. National Academy Press, 1996.Google Scholar
[126] Robbins, H.. Statistical methods related to the law of the iterated logarithm. The Annals of Mathematical Statistics, 41:13971409, 1970.Google Scholar
[127] Robertson, B., Vignaux, G. A., and C. H. Berger. Interpreting Evidence: Evaluating Forensic Science in the Courtroom. Wiley, 2016.Google Scholar
[128] Rohlfs, R. V., Fullerton, S. M., and Weir, B. S.. Familial identification: Population structure and relationship distinguishability. PLoS Genetics, 8(2):e1002469, 2012.Google Scholar
[129] Royall, R.. Statistical Evidence. CRC Press, 1996.Google Scholar
[130] Schauer, F. F.. Profiles, Probabilities and Stereotypes. Harvard University Press, 2003.Google Scholar
[131] Schneider, P. M. et al. Allgemeine Empfehlungen der Spurenkommission zur statistischen Bewertung von DNA-Datenbank Treffern. Rechtsmedizin, 20:111115, 2010.Google Scholar
[132] Shafer, G.. A Mathematical Theory of Evidence. Princeton University Press, 1976.CrossRefGoogle Scholar
[133] Shafer, G.. Constructive Probability. Synthese, 48(1):160, 1981.Google Scholar
[134] Shafer, G.. Non-additive probabilities in the work of Bernoulli and Lambert. In Yager, Ronald R. and Liu, Liping (eds.), Classic Works of the Dempster–Shafer Theory of Belief Functions, pages 117–181. Springer, 2008.Google Scholar
[135] Sjerps, M.. The role of statistics in forensic science casework and research. Problems of Forensic Sciences, LXV:82–90, 2006.Google Scholar
[136] Sjerps, M. and Meester, R.. Selection effects and database screening in forensic science. Forensic Science International, 192:5661, 2009.Google Scholar
[137] Sjerps, M. J., Alberink, I., Bolck, A., Stoel, R. D., Vergeer, P., and Van Zanten, J. H.. Uncertainty and LR: To integrate or not to integrate, that’s the question. Law, Probability and Risk, 15:2329, 2015.Google Scholar
[138] Slooten, K.. Familial searching on DNA mixtures with dropout. Forensic Science International: Genetics, 22:128138, 2016.Google Scholar
[139] Slooten, K.. Accurate assessment of the weight of evidence for DNA mixtures by integrating the likelihood ratio. Forensic Science International: Genetics, 27:116, 2017.Google Scholar
[140] Slooten, K.. The information gain from peak height data in DNA mixtures. Forensic Science International: Genetics, 36:119123, 2018.Google Scholar
[141] Slooten, K.. A top-down approach to DNA mixtures. Forensic Science International: Genetics, 46:114, 2020.Google Scholar
[142] Slooten, K. and Berger, C. E. H.. Response paper to “The likelihood of encapsulating all uncertainty”: the relevance of additional information for the LR. Science and Justice, 57:468471, 2017.Google Scholar
[143] Slooten, K. and Caliebe, A.. Contributors are a nuisance (parameter) for DNA mixture evidence evaluation. Forensic Science International: Genetics, 37:116125, 2018.Google Scholar
[144] Slooten, K. and Egeland, T.. Exclusion probabilities and likelihood ratios with applications to kinship problems. International Journal of Legal Medicine, 128(3):415425, 2014.Google Scholar
[145] Slooten, K. and Egeland, T.. The likelihood ratio as a random variable for linked markers in kinship analysis. International Journal of Legal Medicine, 130(6):14451456, 2016.Google Scholar
[146] Slooten, K. and Meester, R.. Forensic identification: The island problem and its generalizations. Statistica Neerlandica, 65:202237, 2011.Google Scholar
[147] Slooten, K. and Meester, R.. Statistical aspects of familial searching. Forensic Science International: Genetics Supplement Series, 3:e617–e619, 2011.Google Scholar
[148] Slooten, K. and Meester, R.. Probabilistic strategies for familial DNA searching. Journal of the Royal Statistical Society: Series C (Applied Statistics), 63(3):361–384, 2014.Google Scholar
[149] Smith, M.. When does evidence suffice for conviction? Mind, 127:11931218, 2018.Google Scholar
[150] Steele, C. D., Greenhalgh, M., and Balding, D. J.. Evaluation of low-template DNA profiles using peak heights. Statistical Applications of Genetics and Molecular Biology, 15(5):431445, 2016.Google Scholar
[151] Stockmarr, A.. Likelihood ratios for evaluating DNA evidence when the suspect is found through a database search. Biometrics, 55(3): 671677, 1999.Google Scholar
[152] Storvik, G. and Egeland, T.. The DNA database search controversy revisited: Bridging the Bayesian–Frequentist gap. Biometrics, 63:922925, 2007.Google Scholar
[153] Suter, S.. All in the family: Privacy and DNA familial searching. Harvard Journal of Law & Technology, 23(2):309399, 2010.Google Scholar
[154] Swaminathan, H., Garg, A., Grgicak, C. M., Medard, M., and Lun, D. S.. CEESIt: A computational tool for the interpretation of STR mixtures. Forensic Science International: Genetics, 22:149160, 2016.Google Scholar
[155] SWGDAM Interpretation Guidelines for Autosomal STR Typing by Forensic DNA Testing Laboratories. Available online: www.swgdam.org/publications. SWGDAM, 2017.Google Scholar
[156] Swinburne, R.. An Introduction to Confirmation Theory. Methuen, 1973.Google Scholar
[157] Taroni, F., Biedermann, A., Garbolino, P., and Bozza, S.. Reconciliation of subjective probabilities and frequencies in forensic science. Law, Probability and Risk, 17:243262, 2018.Google Scholar
[158] Taroni, F., Bozza, S., Biedermann, A., and Aitken, C.. Dismissal of the illusion of uncertainty in the assessment of a likelihood ratio. Law, Probability and Risk, (15):116, 2015.Google Scholar
[159] Taroni, F., Lambert, J. A., Fereday, L., and Werrett, D. J.. Evaluation and presentation of forensic DNA evidence in European laboratories. Science and Justice, 42:2128, 2002.Google Scholar
[160] Taylor, D., Bright, J., and Buckleton, J.. The interpretation of single source and mixed DNA profiles. Forensic Science International: Genetics, 7(5):516528, 2013.Google Scholar
[161] Taylor, D., Hicks, T., and Champod, C.. Using sensitivity analysis in Bayesian networks to highlight the impact of data paucity and direct future analysis: A contribution to the debate on measuring and reporting the precision of likelihood ratios. Science and Justice, 56:402410, 2016.Google Scholar
[162] Tillmar, A. O. and Mostad, P.. Choosing supplementary markers in forensic casework. Forensic Science International: Genetics, 13:128133, 2014.Google Scholar
[163] Van Trees, H. L.. Detection, Estimation, and Modulation Theory, Part I. Wiley, 2001.Google Scholar
[164] Triggs, C. M. and Buckleton, J. S.. The two trace transfer problem re-examined. Science and Justice, 43:127134, 2003.Google Scholar
[165] Twelve Guiding Principles and Recommendations for Dealing with Quantitative Evidence in Criminal Law. Available online: www.newton.ac.uk/files/preprints/ni16061.pdf. Isaac Newton Institute for Mathematical Sciences, 2017.Google Scholar
[166] Verma, T. and Pearl, J.. Causal networks: Semantics and expressiveness. Uncertainty in Arificial Intelligence, 9:6976, 1990.Google Scholar
[167] Verma, T. and J. Pearl. Equivalence and synthesis of causal models. UAI’90: Proceedings of the Sixth Annual Conference on Uncertainty in Artificial intelligence, pages 255–268, 1990.Google Scholar
[168] Ville, J.. Etude Critique de la Notion de Collectif. Gauthier-Villers, 1939.Google Scholar
[169] Vlek, C., Prakken, H., Renooij, H., and Verheij, B.. Modeling crime scenarios in a Bayesian network. ICAIL. ACM, Rome, 2013.Google Scholar
[170] Vlek, C., Prakken, H., Renooij, H., and Verheij, B.. Representing the quality of crime scenarios in a Bayesian network. JURIX: The 28th Annual Conference, 2015.Google Scholar
[171171] Vlek, C., Prakken, H., and Verheij, B.. A method for explaining Bayesian networks for legal evidence with scenarios. Artificial Intelligence and Law, 24:285324, 2016.Google Scholar
[172] Walley, P.. Statistical Reasoning with Imprecise Probabilities. Chapman and Hall, 1991.Google Scholar
[173] Wasserman, D. T.. The morality of statistical proof and the risk of mistaken liability. Cardozo Law Review, 13:935976, 1991.Google Scholar
[174] Weir, B. S.. The second National Research Council report on forensic DNA evidence. The American Journal of Human Genetics, 59:497500, 1996.Google Scholar
[175] Weir, B. S.. The consequence of defending DNA statistics. In Gastwirth, J. (ed.), Statistical Science in the Courtroom: Statistics for Social Science and Public Policy, pages 87–97, Springer, 2000.Google Scholar
[176] Weir, B. S. and Cockerham, C. C.. Estimating F-Statistics for the analysis of population structure. Evolution, 38(6):13581370, 1984.Google Scholar
[177] Westen, A. et al. Comparing six commercial autosomal STR kits in a large Dutch population sample. Forensic Science International: Genetics, 10:5523, 2014.Google Scholar
[178] Wixted, J. T., Christenfeld, N. J. S., and Rouder, J. N.. Calculating the posterior odds from a single-match DNA database search. Law, Probability and Risk, 18:123, 2019.Google Scholar
[179] Yellin, J.. Review of Evidence, proof and probability (by Richard Eggleston). Journal of Economic Literature, 17(2):583584, 1979.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • References
  • Ronald Meester, Vrije Universiteit, Amsterdam, Klaas Slooten, Vrije Universiteit, Amsterdam
  • Book: Probability and Forensic Evidence
  • Online publication: 09 April 2021
  • Chapter DOI: https://doi.org/10.1017/9781108596176.016
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • References
  • Ronald Meester, Vrije Universiteit, Amsterdam, Klaas Slooten, Vrije Universiteit, Amsterdam
  • Book: Probability and Forensic Evidence
  • Online publication: 09 April 2021
  • Chapter DOI: https://doi.org/10.1017/9781108596176.016
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • References
  • Ronald Meester, Vrije Universiteit, Amsterdam, Klaas Slooten, Vrije Universiteit, Amsterdam
  • Book: Probability and Forensic Evidence
  • Online publication: 09 April 2021
  • Chapter DOI: https://doi.org/10.1017/9781108596176.016
Available formats
×