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Journal of Data Science, 23 (3/4)

  • 1.  Journal of Data Science, 23 (3/4)

    Posted 6 hours ago
    Dear Colleagues,

    As the holiday season approaches, I am pleased to share the final two issues of Volume 23 of the Journal of Data Science (https://jds-online.org). Issue 3 features selected contributions from the 2024 WNAR/IMS/Graybill Annual Meeting and was co-guest-edited by Tianjian Zhou (Colorado State University), Brian Wiens (Rivus Pharmaceuticals), and Tianying Wang (Colorado State University). Issue 4 is a special issue on "Statistical Frontiers of Data Science," co-guest-edited by Xiaoling Lu (Renmin University of China), Yixuan Qiu (Shanghai University of Finance and Economics), Zhezhen Jin (Columbia University), Chunming Zhang (University of Wisconsin-Madison), and Wenxuan Zhong (University of Georgia). We sincerely thank all guest editors, reviewers, and contributing authors for their dedication and hard work in making these issues 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.

    With best wishes for the holiday season and the coming year,
    Jun Yan
    Editor, Journal of Data Science
    =======
    # 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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/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. https://doi.org/10.6339/24-JDS1157

    # Journal of Data Science, Volume 23, Issue 4, 2025

    Lu, X., Qiu, Y., Jin, Z., Zhang, C., & Zhong, W. (2025). Editorial: Statistical Frontiers of Data Science. Journal of Data Science, 23(4), 575-577. https://doi.org/10.6339/25-JDS234EDI

    Lu, H., Cheng, H., Wang, Y., Xie, Y., Yan, H., Wang, X., Ma, P., & Zhong, W. (2025). Mortgage Prepayment Modeling via a Smoothing Spline State Space Model. Journal of Data Science, 23(4), 578-591. https://doi.org/10.6339/25-JDS1165

    Cai, M., Zhao, K., Huang, P., Celedón, J. C., McKennan, C., Chen, W., & Wang, J. (2025). EMixed: Probabilistic Multi-Omics Cellular Deconvolution of Bulk Omics Data. Journal of Data Science, 23(4), 592-606. https://doi.org/10.6339/25-JDS1170

    Li, Y., Alemdjrodo, K., Lin, Y., Zhang, M., & Zhang, D. (2025). Exploring Massive Risk Factors of Categorical Outcomes via Supervised Dimension Reduction. Journal of Data Science, 23(4), 607-623. https://doi.org/10.6339/25-JDS1188

    Zhou, R., He, K., Wang, D., Liu, L., Ma, S., Qu, A., Miller, J., & Liu, L. (2025). Neural Network for Correlated Survival Outcomes Using Frailty Model. Journal of Data Science, 23(4), 624-637. https://doi.org/10.6339/25-JDS1173

    Zhang, X., & Ma, C. (2025). Analysis of Bilateral and Unilateral Data: A Comparative Review of Model-Based and MLE-Based Methods for the Homogeneity Test of Proportions. Journal of Data Science, 23(4), 638-647. https://doi.org/10.6339/25-JDS1168

    Gao, T., Dai, B., & Qiu, Y. (2025). ReLU-ReHU Representations of Piecewise Linear-Quadratic Losses. Journal of Data Science, 23(4), 648-658. https://doi.org/10.6339/24-JDS1162

    Shao, Q. (2025). Interval Forecasting in Time Series Analysis: Application to COVID-19 and Beyond. Journal of Data Science, 23(4), 659-675. https://doi.org/10.6339/25-JDS1187

    Zhang, C., Zhang, Z., Zhong, X., Li, J., & Zhao, Z. (2025). A Statistician's Selective Review of Neural Network Modeling: Algorithms and Applications. Journal of Data Science, 23(4), 676-694. https://doi.org/10.6339/25-JDS1167

    Liu, M., Li, J., Wei, T., Wang, X., & Lu, X. (2025). A Journey of Wisdom and Impact: A Conversation with Dr. Xizhi Wu. Journal of Data Science, 23(4), 695-715. https://doi.org/10.6339/25-JDS1204


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