| Building a unified statistical framework for the forensic identification of source problems DM Ommen, CP Saunders Law, Probability and Risk 17 (2), 179-197, 2018 | 46 | 2018 |
| An argument against presenting interval quantifications as a surrogate for the value of evidence DM Ommen, CP Saunders, C Neumann Science & Justice 56 (5), 383-387, 2016 | 30 | 2016 |
| The characterization of Monte Carlo errors for the quantification of the value of forensic evidence DM Ommen, CP Saunders, C Neumann Journal of Statistical Computation and Simulation 87 (8), 1608-1643, 2017 | 26 | 2017 |
| A problem in forensic science highlighting the differences between the Bayes factor and likelihood ratio DM Ommen, CP Saunders Statistical Science 36 (3), 344-359, 2021 | 19 | 2021 |
| Score-based likelihood ratios to evaluate forensic pattern evidence N Garton, D Ommen, J Niemi, A Carriquiry arXiv preprint arXiv:2002.09470, 2020 | 12 | 2020 |
| Approximate statistical solutions to the forensic identification of source problem DM Ommen South Dakota State University, 2017 | 10 | 2017 |
| Handwriting identification using random forests and score‐based likelihood ratios MQ Johnson, DM Ommen Statistical Analysis and Data Mining: The ASA Data Science Journal 15 (3 …, 2022 | 9 | 2022 |
| Advances toward validating examiner writership opinion based on handwriting kinematics DM Ommen, C Fuglsby, MP Caligiuri Forensic Science International 318, 110644, 2021 | 9 | 2021 |
| Characterization and differentiation of aluminum powders used in improvised explosive devices–Part 1: Proof of concept of the utility of particle micromorphometry JM Baldaino, DM Ommen, CP Saunders, J Hietpas, JA Buscaglia Journal of forensic sciences 66 (1), 83-95, 2021 | 6 | 2021 |
| Characterization and differentiation of aluminum powders used in improvised explosive devices. Part 2: Micromorphometric method refinement and preliminary statistical analysis DM Ommen, JM Baldaino, CP Saunders, J Hietpas, JA Buscaglia Journal of forensic sciences 67 (2), 505-515, 2022 | 5 | 2022 |
| Use of an Automated System to Evaluate Feature Dissimilarities in Handwriting Under a Two‐Stage Evaluative Process*,† C Fuglsby, C Saunders, DM Ommen, MP Caligiuri Journal of Forensic Sciences 65 (6), 2080-2086, 2020 | 5 | 2020 |
| Source‐anchored, trace‐anchored, and general match score‐based likelihood ratios for camera device identification S Reinders, Y Guan, D Ommen, J Newman Journal of Forensic Sciences 67 (3), 975-988, 2022 | 4 | 2022 |
| Elucidating the relationships between two automated handwriting feature quantification systems for multiple pairwise comparisons C Fuglsby, C Saunders, DM Ommen, JA Buscaglia, MP Caligiuri Journal of Forensic Sciences 67 (2), 642-650, 2022 | 4 | 2022 |
| Reconciling the Bayes Factor and Likelihood Ratio for Two Non-Nested Model Selection Problems DM Ommen, CP Saunders arXiv preprint arXiv:1901.09798, 2019 | 4 | 2019 |
| Generalized fiducial factor: An alternative to the Bayes factor for forensic identification of source problems JP Williams, DM Ommen, J Hannig The Annals of Applied Statistics 17 (1), 378-402, 2023 | 3 | 2023 |
| A Note on the specific source identification problem in forensic science in the presence of uncertainty about the background population DM Ommen, CP Saunders, C Neumann arXiv preprint arXiv:1503.08234, 2015 | 3 | 2015 |
| Ensemble learning for score likelihood ratios under the common source problem F Veneri, DM Ommen Statistical Analysis and Data Mining: The ASA Data Science Journal 16 (6 …, 2023 | 2 | 2023 |
| A statistical approach to aid examiners in the forensic analysis of handwriting AM Crawford, DM Ommen, AL Carriquiry Journal of Forensic Sciences 68 (5), 1768-1779, 2023 | 2 | 2023 |
| A rotation-based feature and Bayesian hierarchical model for the forensic evaluation of handwriting evidence in a closed set AM Crawford, DM Ommen, AL Carriquiry The Annals of Applied Statistics 17 (2), 1127-1151, 2023 | 2 | 2023 |
| An evaluation of score-based likelihood ratios for glass data F Veneri, D Ommen | 2 | 2021 |
Chris SaundersSouth Dakota State UniversityVerified email at sdstate.edu
