{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:05:41Z","timestamp":1792785941396,"version":"4.5.0"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T00:00:00Z","timestamp":1787961600000},"content-version":"vor","delay-in-days":11,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"U Bremen Research Alliance\/AI Center for Health Care"},{"name":"Federal State of Bremen","id":[{"id":"https:\/\/ror.org\/03xhyan61","id-type":"ROR","asserted-by":"crossref"}]},{"name":"the European Union\u2019s ERASMUS"},{"DOI":"10.13039\/501100000196","name":"Canada Foundation for Innovation","doi-asserted-by":"publisher","award":["36619"],"award-info":[{"award-number":["36619"]}],"id":[{"id":"10.13039\/501100000196","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000024","name":"Canadian Institutes of Health Research","doi-asserted-by":"publisher","award":["376067"],"award-info":[{"award-number":["376067"]}],"id":[{"id":"10.13039\/501100000024","id-type":"DOI","asserted-by":"publisher"}]},{"name":"German Research Foundation","award":["499552394"],"award-info":[{"award-number":["499552394"]}],"id":[{"id":"https:\/\/ror.org\/018mejw64","id-type":"ROR","asserted-by":"crossref"}]},{"name":"NFDI4Health"},{"DOI":"10.13039\/100004807","name":"DFG","doi-asserted-by":"publisher","award":["442326535"],"award-info":[{"award-number":["442326535"]}],"id":[{"id":"10.13039\/100004807","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Culture and Science of North Rhine-Westphalia and the Federal Ministry of Research, Technology and Space of Germany","id":[{"id":"https:\/\/ror.org\/04pz7b180","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Synthetic data hold substantial potential to address practical challenges in epidemiology due to restricted data access and privacy concerns. However, many current methods suffer from limited quality, high computational demands, and complexity for non-experts. Furthermore, common evaluation strategies for synthetic data often fail to directly reflect statistical utility and measure privacy risks sufficiently. Against this background, a critical underexplored question is whether synthetic data can reliably reproduce key findings from epidemiological research while preserving privacy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We propose adversarial random forests (ARF) as an efficient and convenient method for synthesizing tabular epidemiological data. To evaluate its performance, we replicated statistical analyses from six epidemiological publications covering blood pressure, anthropometry, myocardial infarction, accelerometry, loneliness, and diabetes, from the German National Cohort (NAKO Gesundheitsstudie), the Bremen STEMI Registry U45 Study, and the Guelph Family Health Study. We further assessed how dataset dimensionality and variable complexity affect the quality of synthetic data, and contextualized ARF\u2019s performance by comparison with commonly used tabular data synthesizers in terms of utility, privacy, generalization, and runtime.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Across all replicated studies, results on ARF-generated synthetic data consistently aligned with original findings. Even for datasets with relatively low sample size-to-dimensionality ratios, replication outcomes closely matched the original results across descriptive and inferential analyses. Reduced dimensionality and variable complexity further enhanced synthesis quality. ARF demonstrated favourable performance regarding utility, privacy preservation, and generalization relative to other synthesizers and superior computational efficiency.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In summary, ARF reliably generates high-quality synthetic data that replicate diverse epidemiological analyses while offering a competitive privacy\u2013utility trade-off.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ije\/dyag164","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T11:36:40Z","timestamp":1786448200000},"source":"Crossref","is-referenced-by-count":0,"title":["Can synthetic data reproduce real-world findings in epidemiology? A replication study using adversarial random forests"],"prefix":"10.1093","volume":"55","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-6408-2840","authenticated-orcid":false,"given":"Jan","family":"Kapar","sequence":"first","affiliation":[{"name":"Leibniz Institute for Prevention Research and Epidemiology\u2014BIPS , Bremen,","place":["Germany"]},{"name":"Faculty of Mathematics and Computer Science, University of Bremen , Bremen,","place":["Germany"]},{"name":"Department of Human Health Sciences, University of Guelph , Guelph, Ontario,","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3801-4769","authenticated-orcid":false,"given":"Kathrin","family":"G\u00fcnther","sequence":"additional","affiliation":[{"name":"Leibniz Institute for Prevention Research and Epidemiology\u2014BIPS , Bremen,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3970-9159","authenticated-orcid":false,"given":"Lori Ann","family":"Vallis","sequence":"additional","affiliation":[{"name":"Department of Human Health Sciences, University of Guelph , Guelph, Ontario,","place":["Canada"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Klaus","family":"Berger","sequence":"additional","affiliation":[{"name":"Institute of Epidemiology and Social Medicine, University of M\u00fcnster , M\u00fcnster,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nadine","family":"Binder","sequence":"additional","affiliation":[{"name":"Institute of General Practice\/Family Medicine, Faculty of Medicine and Medical Center, University of Freiburg , Freiburg,","place":["Germany"]},{"name":"Freiburg Center for Data Analysis, Modeling and AI, University of Freiburg , Freiburg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hermann","family":"Brenner","sequence":"additional","affiliation":[{"name":"Cancer Prevention Graduate School, German Cancer Research Center (DKFZ) , Heidelberg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefanie","family":"Castell","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Helmholtz Centre for Infection Research (HZI) , Brunswick,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beate","family":"Fischer","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Preventive Medicine, University of Regensburg , Regensburg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Volker","family":"Harth","sequence":"additional","affiliation":[{"name":"Institute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf , Hamburg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernd","family":"Holleczek","sequence":"additional","affiliation":[{"name":"Saarland Cancer Registry , Saarbr\u00fccken,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timm","family":"Intemann","sequence":"additional","affiliation":[{"name":"Leibniz Institute for Prevention Research and Epidemiology\u2014BIPS , Bremen,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Till","family":"Ittermann","sequence":"additional","affiliation":[{"name":"Institute for Community Medicine, University Medicine Greifswald , Greifswald,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andr\u00e9","family":"Karch","sequence":"additional","affiliation":[{"name":"Institute of Epidemiology and Social Medicine, University of M\u00fcnster , M\u00fcnster,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Keil","sequence":"additional","affiliation":[{"name":"Institute of Social Medicine, Epidemiology and Health Economics, Charit\u00e9 Universit\u00e4tsmedizin Berlin , Berlin,","place":["Germany"]},{"name":"Institute of Clinical Epidemiology and Biometry, University of W\u00fcrzburg , W\u00fcrzburg,","place":["Germany"]},{"name":"State Institute of Health I, Bavarian Health and Food Safety Authority , Erlangen,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lilian","family":"Krist","sequence":"additional","affiliation":[{"name":"Institute of Social Medicine, Epidemiology and Health Economics, Charit\u00e9 Universit\u00e4tsmedizin Berlin , Berlin,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Berit","family":"Lange","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Helmholtz Centre for Infection Research (HZI) , Brunswick,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael F","family":"Leitzmann","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Preventive Medicine, University of Regensburg , Regensburg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katharina","family":"Nimptsch","sequence":"additional","affiliation":[{"name":"Molecular Epidemiology Research Group, Max Delbr\u00fcck Center for Molecular Medicine in the Helmholtz Association (MDC) , Berlin,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nadia","family":"Obi","sequence":"additional","affiliation":[{"name":"Institute for Occupational and Maritime Medicine (ZfAM), University Medical Center Hamburg-Eppendorf , Hamburg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iris","family":"Pigeot","sequence":"additional","affiliation":[{"name":"Leibniz Institute for Prevention Research and Epidemiology\u2014BIPS , Bremen,","place":["Germany"]},{"name":"Faculty of Mathematics and Computer Science, University of Bremen , Bremen,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tobias","family":"Pischon","sequence":"additional","affiliation":[{"name":"Molecular Epidemiology Research Group, Max Delbr\u00fcck Center for Molecular Medicine in the Helmholtz Association (MDC) , Berlin,","place":["Germany"]},{"name":"Biobank Technology Platform, Max Delbr\u00fcck Center for Molecular Medicine in the Helmholtz Association (MDC) , Berlin,","place":["Germany"]},{"name":"Charit\u00e9 \u2013 Universit\u00e4tsmedizin Berlin, corporate member of Freie Universit\u00e4t Berlin and Humboldt-Universit\u00e4t zu Berlin , Berlin,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tamara","family":"Schikowski","sequence":"additional","affiliation":[{"name":"IUF\u2014Leibniz Research Institute for Environmental Medicine , D\u00fcsseldorf,","place":["Germany"]},{"name":"Department of Environment and Health, School of Public Health, University of Bielefeld , Bielefeld,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"B\u00f6rge","family":"Schmidt","sequence":"additional","affiliation":[{"name":"Institute for Medical Informatics, Biometry and Epidemiology, University Hospital of Essen, University of Duisburg , Essen,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carsten Oliver","family":"Schmidt","sequence":"additional","affiliation":[{"name":"Institute for Community Medicine, University Medicine Greifswald , Greifswald,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anja M","family":"Sedlmair","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Preventive Medicine, University of Regensburg , Regensburg,","place":["Germany"]},{"name":"Center for Translational Oncology, University Hospital Regensburg , Regensburg,","place":["Germany"]},{"name":"Bavarian Cancer Research Center (BZKF) , Regensburg,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Justine","family":"Tanoey","sequence":"additional","affiliation":[{"name":"Leibniz Institute for Prevention Research and Epidemiology\u2014BIPS , Bremen,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Harm","family":"Wienbergen","sequence":"additional","affiliation":[{"name":"Bremen Institute for Heart and Circulation Research (BIHKF) , Bremen,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andreas","family":"Wienke","sequence":"additional","affiliation":[{"name":"Institute of Medical Epidemiology, Biometry, and Informatics, Profile Center Health Sciences, Faculty of Medicine, Martin Luther University Halle-Wittenberg , Halle,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudia","family":"Wigmann","sequence":"additional","affiliation":[{"name":"IUF\u2014Leibniz Research Institute for Environmental Medicine , D\u00fcsseldorf,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8542-6291","authenticated-orcid":false,"given":"Marvin N","family":"Wright","sequence":"additional","affiliation":[{"name":"Leibniz Institute for Prevention Research and Epidemiology\u2014BIPS , Bremen,","place":["Germany"]},{"name":"Faculty of Mathematics and Computer Science, University of Bremen , Bremen,","place":["Germany"]},{"name":"Department of Public Health, University of Copenhagen , Copenhagen,","place":["Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,8,29]]},"reference":[{"key":"2026092402422321500_dyag164-B1","author":"Centers for Disease Control and Prevention (U.S.)"},{"key":"2026092402422321500_dyag164-B2","author":"European Parliament and Council of the European Union","year":"2016"},{"key":"2026092402422321500_dyag164-B3","volume-title":"Generative Deep Learning","author":"Foster","year":"2022"},{"key":"2026092402422321500_dyag164-B4","author":"OpenAI"},{"key":"2026092402422321500_dyag164-B5","author":"OpenAI"},{"key":"2026092402422321500_dyag164-B6","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1007\/s10278-021-00556-w","article-title":"Systematic review of generative adversarial networks (GANs) for medical image classification and segmentation","volume":"35","author":"Jeong","year":"2022","journal-title":"J Digit Imaging"},{"key":"2026092402422321500_dyag164-B7","doi-asserted-by":"publisher","first-page":"e102846","DOI":"10.1016\/j.media.2023.102846","article-title":"Diffusion models in medical imaging: a comprehensive survey","volume":"88","author":"Kazerouni","year":"2023","journal-title":"Med Image Anal"},{"key":"2026092402422321500_dyag164-B8","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/978-3-031-69651-0_8","article-title":"Generating synthetic data is complicated: know your data and know your generator","volume":"14915","author":"Latner","year":"2024","journal-title":"Priv Stat Databases"},{"key":"2026092402422321500_dyag164-B9","doi-asserted-by":"publisher","first-page":"e14412","DOI":"10.1038\/s41598-024-62102-2","article-title":"Synthetic data generation for a longitudinal cohort study\u2014evaluation, method extension and reproduction of published data analysis results","volume":"14","author":"K\u00fchnel","year":"2024","journal-title":"Sci Rep"},{"key":"2026092402422321500_dyag164-B10","doi-asserted-by":"publisher","first-page":"e6978","DOI":"10.1038\/s41598-024-57207-7","article-title":"An evaluation of the replicability of analyses using synthetic health data","volume":"14","author":"El Emam","year":"2024","journal-title":"Sci Rep"},{"key":"2026092402422321500_dyag164-B11","article-title":"Modeling tabular data using conditional GAN","volume":"32","author":"Xu","year":"2019","journal-title":"Adv Neural Inf Process Syst"},{"key":"2026092402422321500_dyag164-B12","doi-asserted-by":"publisher","first-page":"3173","DOI":"10.52202\/075280-0140","article-title":"Synthcity: a benchmark framework for diverse use cases of tabular synthetic data","volume":"36","author":"Qian","year":"2023","journal-title":"Adv Neural Inf Process Syst"},{"key":"2026092402422321500_dyag164-B13","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1007\/978-3-032-07884-1_24","article-title":"The DCR delusion: measuring the privacy risk of synthetic data","author":"Yao","year":"2025","journal-title":"Eur Symp Res Comput Secur"},{"key":"2026092402422321500_dyag164-B14","first-page":"5357","article-title":"Adversarial random forests for density estimation and generative modeling","volume":"206","author":"Watson","year":"2023","journal-title":"AISTATS"},{"key":"2026092402422321500_dyag164-B15","volume-title":"arf: Adversarial Random Forests","author":"Wright","year":"2024"},{"key":"2026092402422321500_dyag164-B16","doi-asserted-by":"publisher","first-page":"452","DOI":"10.1007\/s00103-020-03109-8","article-title":"Blutdruckmessung in der NAKO\u2014methodische Unterschiede, Blutdruckverteilung und Bekanntheit der Hypertonie im Vergleich zu anderen bev\u00f6lkerungsbezogenen Studien in Deutschland [Blood pressure measurement in the NAKO German National Cohort (GNC)\u2014differences in methods, distribution of blood pressure values, and awareness of hypertension compared to other population-based studies in Germany]","volume":"63","author":"Schikowski","year":"2020","journal-title":"Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz"},{"key":"2026092402422321500_dyag164-B17","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1007\/s00103-020-03096-w","article-title":"Anthropometrische Messungen in der NAKO Gesundheitsstudie\u2014mehr als als nur Gr\u00f6\u00dfe und Gewicht [Anthropometric measures in the German National Cohort\u2014more than weight and height]","volume":"63","author":"Fischer","year":"2020","journal-title":"Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz"},{"key":"2026092402422321500_dyag164-B18","doi-asserted-by":"publisher","first-page":"2076","DOI":"10.1093\/eurjpc\/zwac132","article-title":"Lifestyle and metabolic risk factors in patients with early-onset myocardial infarction: a case-control study","volume":"29","author":"Wienbergen","year":"2022","journal-title":"Eur J Prev Cardiol"},{"key":"2026092402422321500_dyag164-B19","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1123\/jmpb.2021-0042","article-title":"ActiGraph cutpoints impact physical activity and sedentary behavior outcomes in young children","volume":"5","author":"Breau","year":"2022","journal-title":"J Meas Phys Behav"},{"key":"2026092402422321500_dyag164-B20","doi-asserted-by":"publisher","first-page":"1157","DOI":"10.1007\/s00103-021-03393-y","article-title":"Einsamkeit w\u00e4hrend der ersten Welle der SARS-CoV-2-Pandemie\u2014Ergebnisse der NAKO-Gesundheitsstudie [Loneliness during the first wave of the SARS-CoV-2 pandemic\u2014results of the German National Cohort (NAKO)]","volume":"64","author":"Berger","year":"2021","journal-title":"Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz"},{"key":"2026092402422321500_dyag164-B21","doi-asserted-by":"publisher","first-page":"e10880","DOI":"10.3390\/ijerph191710880","article-title":"Birth order, caesarean section, or daycare attendance in relation to child-and adult-onset type 1 diabetes: results from the German National Cohort","volume":"19","author":"Tanoey","year":"2022","journal-title":"Int J Environ Res Public Health"},{"key":"2026092402422321500_dyag164-B22","doi-asserted-by":"publisher","first-page":"1107","DOI":"10.1007\/s10654-022-00890-5","article-title":"Framework and baseline examination of the German National Cohort (NAKO)","volume":"37","author":"Peters","year":"2022","journal-title":"Eur J Epidemiol"},{"key":"2026092402422321500_dyag164-B23","doi-asserted-by":"publisher","first-page":"549","DOI":"10.17269\/s41997-018-0072-3","article-title":"Guelph Family Health Study: pilot study of a home-based obesity prevention intervention","volume":"109","author":"Haines","year":"2018","journal-title":"Can J Public Health"},{"key":"2026092402422321500_dyag164-B24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v074.i11","article-title":"synthpop: bespoke creation of synthetic data in R","volume":"74","author":"Nowok","year":"2016","journal-title":"J Stat Softw"},{"key":"2026092402422321500_dyag164-B25","volume-title":"Probabilistic Graphical Models: Principles and Techniques","author":"Koller","year":"2009"},{"key":"2026092402422321500_dyag164-B26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3134428","article-title":"PrivBayes: private data release via Bayesian networks","volume":"42","author":"Zhang","year":"2017","journal-title":"ACM Trans Database Syst"},{"key":"2026092402422321500_dyag164-B27","doi-asserted-by":"publisher","first-page":"7499","DOI":"10.1109\/TNNLS.2022.3229161","article-title":"Deep neural networks and tabular data: a survey","volume":"35","author":"Borisov","year":"2024","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"2026092402422321500_dyag164-B28","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1145\/3712311.3712315","article-title":"Navigating tabular data synthesis research understanding user needs and tool capabilities","volume":"53","author":"Davila R","year":"2025","journal-title":"SIGMOD Rec"},{"key":"2026092402422321500_dyag164-B29","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1023\/A:1022643204877","article-title":"Induction of decision trees","volume":"1","author":"Quinlan","year":"1986","journal-title":"Mach Learn"},{"key":"2026092402422321500_dyag164-B30","doi-asserted-by":"publisher","first-page":"507","DOI":"10.52202\/068431-0037","article-title":"Why do tree-based models still outperform deep learning on typical tabular data?","volume":"35","author":"Grinsztajn","year":"2022","journal-title":"Adv Neural Inf Process Syst"},{"key":"2026092402422321500_dyag164-B31","doi-asserted-by":"publisher","first-page":"3232","DOI":"10.1016\/j.csda.2011.06.006","article-title":"An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets","volume":"55","author":"Drechsler","year":"2011","journal-title":"Comput Stat Data Anal"},{"key":"2026092402422321500_dyag164-B32","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach Learn"},{"key":"2026092402422321500_dyag164-B33","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1214\/aoms\/1177730200","article-title":"Mixture of distributions","volume":"19","author":"Robbins","year":"1948","journal-title":"Ann Math Statist"},{"key":"2026092402422321500_dyag164-B34","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/978-3-031-63800-8_5","article-title":"Countarfactuals\u2014generating plausible model-agnostic counterfactual explanations with adversarial random forests","volume":"2155","author":"Dandl","year":"2024","journal-title":"Explain Artif Intell xAI 2024"},{"key":"2026092402422321500_dyag164-B35","doi-asserted-by":"publisher","first-page":"e70379","DOI":"10.1002\/sim.70379","article-title":"Missing value imputation with adversarial random forests\u2014MissARF","volume":"45","author":"Golchian","year":"2026","journal-title":"Stat Med"},{"key":"2026092402422321500_dyag164-B36","author":"Burakov"},{"key":"2026092402422321500_dyag164-B37","doi-asserted-by":"crossref","DOI":"10.1201\/9780429246593","volume-title":"An Introduction to the Bootstrap","author":"Efron","year":"1994"},{"key":"2026092402422321500_dyag164-B38","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1007\/978-3-031-13945-1_16","article-title":"Challenges in measuring utility for fully synthetic data","volume":"13463","author":"Drechsler","year":"2022","journal-title":"Priv Stat Databases"},{"key":"2026092402422321500_dyag164-B39","first-page":"1451","article-title":"Synthetic data\u2014anonymisation groundhog day","author":"Stadler","year":"2022","journal-title":"Proc USENIX Secur Symp"},{"key":"2026092402422321500_dyag164-B40","volume-title":"Topics in Optimal Transportation","author":"Villani","year":"2021"},{"key":"2026092402422321500_dyag164-B41","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1046\/j.1525-1497.2001.016009606.x","article-title":"The PHQ-9: validity of a brief depression severity measure","volume":"16","author":"Kroenke","year":"2001","journal-title":"J Gen Intern Med"},{"key":"2026092402422321500_dyag164-B42","doi-asserted-by":"publisher","first-page":"1092","DOI":"10.1001\/archinte.166.10.1092","article-title":"A brief measure for assessing generalized anxiety disorder: the GAD-7","volume":"166","author":"Spitzer","year":"2006","journal-title":"Arch Intern Med"},{"key":"2026092402422321500_dyag164-B43","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1561\/0400000042","article-title":"The algorithmic foundations of differential privacy","volume":"9","author":"Dwork","year":"2014","journal-title":"Found Trends Theor Comput Sci"}],"container-title":["International Journal of Epidemiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/ije\/article-pdf\/55\/5\/dyag164\/70870095\/dyag164.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/ije\/article-pdf\/55\/5\/dyag164\/70870095\/dyag164.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T06:42:31Z","timestamp":1790232151000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/ije\/article\/doi\/10.1093\/ije\/dyag164\/8776068"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,18]]},"references-count":43,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2026,8,18]]}},"URL":"https:\/\/doi.org\/10.1093\/ije\/dyag164","relation":{},"ISSN":["0300-5771","1464-3685"],"issn-type":[{"value":"0300-5771","type":"print"},{"value":"1464-3685","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,10]]},"published":{"date-parts":[[2026,8,18]]},"article-number":"dyag164"}}