学术论文： |
1. Du, M., Wu, Q., Tong, X, and Zhao, X.* (2024). Deep Learning for Regression Analysis of Interval-Censored Failure Time Data. Electronic Journal of Statistics, 18, 4292-4321. 2. Du, M.* and Zhao, X. (2024). A Conditional Approach for Regression Analysis of Case K Interval-Censored Failure Time Data with Informative Censoring. Computational Statistics & Data Analysis, 198, Article 107991. 3. Du, M.*, Gao, X. and Chen, L. (2024). Regression Analysis of Doubly Censored Failure Time Data with Ancillary Information. Life-time Data Analysis, 30, 667-679. 4. Wang, C. and Du, M.*(2024). Martingale-Residuals Greedy Model Averaging for High- Dimensional Current Status Data. Statistics in Medicine, 43, 1726-1742. 5. Lou,Y., Ma, Y. and Du, M.* (2024). A New and Unified Method for Regression Analysis of Interval-Censored Failure Time Data under Semiparametric Transformation Models with Missing Covariates. Statistics in Medicine, 43, 2062-2082. 6. Du, M.* and Zhou, Q. (2023). Analysis of Informatively Interval-Censored Case-Cohort Studies with Application to HIV Vaccine Trials. Communications in Mathematics and Statistics, DOI: https://doi.org/10.1007/s40304-022-00322-6. 7. Du, M.* and Yu, M. (2023). Regression Analysis of Multivariate Interval-Censored Failure Time Data with a Cured Subgroup and Informative Censoring. Journal of Nonparametric Statistics, 36(4), 940-954. 8. Zhang, J., Du, M., Liu, Y.* and Sun, J. (2023). A New Model-Free Feature Screening Procedure for Ultrahigh-Dimensional Interval-Censored Failure Time Data. Statistica Sinica, 33, 1809-1830. 9. Liu, R., Du, M.* and Sun, J. (2023). Variable Selection for Bivariate Interval-censored Failure Time Data under Linear Transformation Models. The International Journal of Bio- statistics, 19 (1), 61-79. 10. Du, M. (2022). Overview of Recent Advances on the Analysis of Interval-Censored Failure Time Data. Emerging Topics in Modeling Interval-Censored Survival Data, edited by Sun, J. and Chen, D. Springer. 11. Du, M., Zhao, X. and Sun, J.* (2022). Variable Selection for Case-Cohort Studies with Informatively Interval-Censored Outcomes. Computational Statistics & Data Analysis, 172, Article 107484. 12. Du, M. and Sun, J.* (2022). Variable Selection for Interval-Censored Failure Time Data. International Statistics Review, 90 (2), 193-215. 13. Yang, D., Du, M.* and Sun, J. (2022). Semiparametric Regression Analysis of Clustered Interval-censored Failure Time Data with a Cured Subgroup. Statistics in Medicine, 40 (30), 6918-6930. 14. Du, M., Zhao, H.* and Sun, J. (2021). A Unified Approach to Variable Selection for Cox's Proportional Hazards Model with Interval-Censored Failure Time Data. Statistical Methods in Medical Research, 30 (8), 1833-1849. 15. Du, M., Li, H. * and Sun, J. (2021). Regression Analysis of Censored Data with Nonig- norable Missing Covariates and Application to Alzheimer's Disease. Computational Statistics & Data Analysis, 157, Article 107157. 16. Du, M., Zhou, Q., Zhao, S. and Sun, J.* (2021). Regression Analysis of Case-cohort Studies in the Presence of Dependent Interval Censoring. Journal of Applied Statistics, 48(5), 846-865. 17. Du, M., Li, H.* and Sun, J. (2020). Additive Hazards Regression for Case-cohort Studies with Interval-censored Data. Statistics and Its Interface, 13(2), 181-191. 18. Du, M., Hu, T.* and Sun, J. (2019). Semiparametric Probit Model for Informative Current Status Data. Statistics in Medicine, 38, 2219-2227. 19. Wang, P., Zhao, H.*, Du, M. and Sun, J. (2018). Inference on Semiparametric Transformation Model with General Interval-censored Failure Time Data. Journal of Nonparametric Statistics, 30, 758-773. |
