Response to: Commentary on: Bright et al. (2018) Internal validation of STRmix™ - A multi laboratory response to PCAST, Forensic Science International: Genetics, 34: 11-24.
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Duncan A. Taylor | Steven M Weitz | J. Buckleton | A. Ciecko | J. Bright | M. Kruijver | T. Bille | Tim Kalafut | T. Moretti | Ben Mallinder | Simon Malsom | Alan Magee | S. Noël | Rachel H Oefelein | Brian Peck | Steven Weitz | Rachel H. Oefelein
[1] Duncan A. Taylor,et al. Testing whether stutter and low-level DNA peaks are additive. , 2019, Forensic science international. Genetics.
[2] Titia Sijen,et al. An assessment of the performance of the probabilistic genotyping software EuroForMix: Trends in likelihood ratios and analysis of Type I & II errors. , 2019, Forensic science international. Genetics.
[3] J. Lefebvre,et al. STRmix™ put to the test: 300 000 non-contributor profiles compared to four-contributor DNA mixtures and the impact of replicates. , 2019, Forensic science international. Genetics.
[4] Jo-Anne Bright,et al. Interpreting a major component from a mixed DNA profile with an unknown number of minor contributors. , 2019, Forensic science international. Genetics.
[5] J. Chaseling,et al. Commentary on: Bright et al. (2018) Internal validation of STRmix™ - a multi laboratory response to PCAST, Forensic Science International: Genetics, 34: 11-24. , 2019, Forensic science international. Genetics.
[6] Duncan A. Taylor,et al. STRmix™ collaborative exercise on DNA mixture interpretation. , 2019, Forensic science international. Genetics.
[7] Jo-Anne Bright,et al. Probabilistic genotyping software: An overview. , 2019, Forensic science international. Genetics.
[8] Jo-Anne Bright,et al. The effect of varying the number of contributors in the prosecution and alternate propositions. , 2019, Forensic science international. Genetics.
[9] E. Alladio,et al. DNA mixtures interpretation - A proof-of-concept multi-software comparison highlighting different probabilistic methods' performances on challenging samples. , 2018, Forensic science international. Genetics.
[10] Bruce Budowle,et al. NIST interlaboratory studies involving DNA mixtures (MIX13): A modern analysis. , 2018, Forensic science international. Genetics.
[11] K Slooten,et al. Contributors are a nuisance (parameter) for DNA mixture evidence evaluation. , 2018, Forensic science international. Genetics.
[12] John M Butler,et al. NIST interlaboratory studies involving DNA mixtures (MIX05 and MIX13): Variation observed and lessons learned. , 2018, Forensic science international. Genetics.
[13] Peter Gill,et al. DNA commission of the International society for forensic genetics: Assessing the value of forensic biological evidence - Guidelines highlighting the importance of propositions: Part I: evaluation of DNA profiling comparisons given (sub-) source propositions. , 2018, Forensic science international. Genetics.
[14] P A Barrio,et al. GHEP-ISFG collaborative exercise on mixture profiles (GHEP-MIX06). Reporting conclusions: Results and evaluation. , 2018, Forensic science international. Genetics.
[15] Duncan A. Taylor,et al. Internal validation of STRmix™ - A multi laboratory response to PCAST. , 2018, Forensic science international. Genetics.
[16] Jo-Anne Bright,et al. Internal validation of STRmix™ for the interpretation of single source and mixed DNA profiles. , 2017, Forensic science international. Genetics.
[17] Duncan A. Taylor,et al. Importance sampling allows Hd true tests of highly discriminating DNA profiles. , 2017, Forensic science international. Genetics.
[18] Øyvind Bleka,et al. A comparative study of qualitative and quantitative models used to interpret complex STR DNA profiles. , 2016, Forensic science international. Genetics.
[19] J Buckleton,et al. DNA Commission of the International Society for Forensic Genetics: Recommendations on the validation of software programs performing biostatistical calculations for forensic genetics applications. , 2016, Forensic science international. Genetics.
[20] Christophe Champod,et al. Using sensitivity analyses in Bayesian Networks to highlight the impact of data paucity and direct future analyses: a contribution to the debate on measuring and reporting the precision of likelihood ratios. , 2016, Science & justice : journal of the Forensic Science Society.
[21] F Taroni,et al. Reframing the debate: A question of probability, not of likelihood ratio. , 2016, Science & justice : journal of the Forensic Science Society.
[22] Geoffrey Stewart Morrison,et al. Special issue on measuring and reporting the precision of forensic likelihood ratios: Introduction to the debate. , 2016, Science & justice : journal of the Forensic Science Society.
[23] James M Curran,et al. Admitting to uncertainty in the LR. , 2016, Science & justice : journal of the Forensic Science Society.
[24] Geoffrey Stewart Morrison,et al. What should a forensic practitioner's likelihood ratio be? , 2016, Science & justice : journal of the Forensic Science Society.
[25] Cedric Neumann,et al. An argument against presenting interval quantifications as a surrogate for the value of evidence. , 2016, Science & justice : journal of the Forensic Science Society.
[26] Charles E H Berger,et al. The LR does not exist. , 2016, Science & justice : journal of the Forensic Science Society.
[27] Ivo Alberink,et al. Posterior distributions for likelihood ratios in forensic science. , 2016, Science & justice : journal of the Forensic Science Society.
[28] T. Sijen,et al. The effect of varying the number of contributors on likelihood ratios for complex DNA mixtures. , 2015, Forensic science international. Genetics.
[29] S. Greenspoon,et al. Establishing the Limits of TrueAllele® Casework: A Validation Study , 2015, Journal of forensic sciences.
[30] Duncan Taylor,et al. Testing likelihood ratios produced from complex DNA profiles. , 2015, Forensic science international. Genetics.
[31] Duncan Taylor,et al. Do low template DNA profiles have useful quantitative data? , 2015, Forensic science international. Genetics.
[32] Duncan Taylor,et al. A series of recommended tests when validating probabilistic DNA profile interpretation software. , 2015, Forensic science international. Genetics.
[33] Jo-Anne Bright,et al. The variability in likelihood ratios due to different mechanisms. , 2015, Forensic science international. Genetics.
[34] Duncan Taylor,et al. Interpreting forensic DNA profiling evidence without specifying the number of contributors. , 2014, Forensic science international. Genetics.
[35] Jo-Anne Bright,et al. Comparison of the performance of different models for the interpretation of low level mixed DNA profiles , 2014, Electrophoresis.
[36] Jo-Anne Bright,et al. The effect of the uncertainty in the number of contributors to mixed DNA profiles on profile interpretation. , 2014, Forensic science international. Genetics.
[37] J Buckleton,et al. An illustration of the effect of various sources of uncertainty on DNA likelihood ratio calculations. , 2014, Forensic science international. Genetics.
[38] Duncan Taylor,et al. Using continuous DNA interpretation methods to revisit likelihood ratio behaviour. , 2014, Forensic science international. Genetics.
[39] P Gill,et al. Euroforgen-NoE collaborative exercise on LRmix to demonstrate standardization of the interpretation of complex DNA profiles. , 2014, Forensic science international. Genetics.
[40] James Curran,et al. Searching mixed DNA profiles directly against profile databases. , 2014, Forensic science international. Genetics.
[41] Joaquin Gonzalez-Rodriguez,et al. Reliable support: Measuring calibration of likelihood ratios. , 2013, Forensic science international.
[42] J. Curran. An introduction to Bayesian credible intervals for sampling error in DNA profiles , 2005 .
[43] James M Curran,et al. What is the magnitude of the subpopulation effect? , 2003, Forensic science international.
[44] D J Balding,et al. DNA profile match probability calculation: how to allow for population stratification, relatedness, database selection and single bands. , 1994, Forensic science international.