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Journal of Data Science 2025, 23(3)

  • 1.  Journal of Data Science 2025, 23(3)

    Posted 10 days ago
    Edited by Tianjian Zhou 10 days ago

    Dear Colleagues,

    The 3rd issue of Volume 23 of the Journal of Data Science has recently been released (https://jds-online.org/journal/JDS/issue/95). This special issue features selected contributions from the 2024 WNAR/IMS/Graybill Annual Meeting, held June 9–12, 2024, on the Colorado State University campus in Fort Collins, Colorado, USA. We extend our sincere thanks to the journal Editor, Jun Yan, for giving us the opportunity to share discussions from the meeting with a broader audience. We are also deeply grateful to the review team and all contributing authors for making this issue possible.

    All articles are published as open access under the CC-BY license (https://creativecommons.org/licenses/by/4.0/) to ensure the widest dissemination. Thanks to funding from the School of Statistics and the Center for Applied Statistics at Renmin University of China, there are no Article Processing Charges. The journal is known for its fast review process and rigorous reproducibility checks.

    Established in 2003, the Journal of Data Science aims to advance and promote data science methods, computing, and applications across all scientific fields where knowledge and insights are to be extracted from data. We welcome submissions to all sections of the journal, including 1) Philosophies of Data Science; 2) Statistical Data Science; 3) Computing in Data Science; 4) Data Science in Action; 5) Data Science Review; 6) Education in Data Science; and 7) Data Science Conversation.

    Best regards,

    Tianjian Zhou, Brian Wiens, and Tianying Wang

    Guest Editors, Journal of Data Science (Special Issue: 2024 WNAR/IMS/Graybill Annual Meeting)

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    Journal of Data Science

    Volume 23, Issue 3, 2025

    Zhou, T., Wiens, B., & Wang, T. (2025). Editorial: 2024 WNAR/IMS/Graybill Annual Meeting. Journal of Data Science, 23(3), 451-453. doi:10.6339/25-JDS233EDI

    Wang, T., Liu, J., & Wu, A. (2025). Bibliographical Connections for Semiparametric Analysis in Case-Control Studies on Gene-Environment Interactions. Journal of Data Science, 23(3), 454-469. doi:10.6339/24-JDS1155

    Jin, Y., & Leroux, A. (2025). Comparing Estimators of Discriminative Performance of Time-to-Event Models. Journal of Data Science, 23(3), 470-490. doi:10.6339/25-JDS1163

    Shan, G. (2025). Restricted Mean Survival Time for a Randomized Study with Survival Outcome. Journal of Data Science, 23(3), 491-498. doi:10.6339/25-JDS1177

    Wang, R., Dai, R., Huang, Y., Neuhouser, M. L., Lampe, J., Raftery, D., Tabung, F. K., & Zheng, C. (2025). Variable Selection with FDR Control for Noisy Data – An Application to Screening Metabolites that Are Associated with Breast Cancer and Colorectal Cancer. Journal of Data Science, 23(3), 499-520. doi:10.6339/25-JDS1166

    Chen, M., Nguyen, T. T., & Liu, J. (2025). High-dimensional Confounding in Causal Mediation: A Comparison Study of Double Machine Learning and Regularized Partial Correlation Network. Journal of Data Science, 23(3), 521-541. doi:10.6339/25-JDS1169

    Pollock, C. P., Hoegh, A., Irvine, K. M., de Wit, L. A., & Reichert, B. E. (2025). Estimating Disease Prevalence from Preferentially Sampled, Pooled Data. Journal of Data Science, 23(3), 542-559. doi:10.6339/25-JDS1191

    Ghosh, I., Zheng, Q., Egger, M. E., & Kong, M. (2025). Estimating Healthcare Expenditure Using Parametric Change Point Models. Journal of Data Science, 23(3), 560-574. doi:10.6339/24-JDS1157



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    Tianjian Zhou
    Assistant Professor
    Colorado State University
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