曲连强 - 华中师范大学 - 数学与统计学学院

个人简介

开设课程本科生: 概率论基础、非参数统计研究生: 统计推断、应用概率论讨论班: Statistical Learning with Sparsity The Lasso and Generalizations, Statistical Methods for Dynamic Treatment Regimes. 工作经历 2017/07-至今: 华中师范大学，讲师 2016/01-2016/03: 香港中文大学统计系，访问学者，香港 2012/09 -2017/07: 中科院数学与系统科学研究院，硕博连读, 导师: 孙六全研究员 2008/09-2012/07: 山东农业大学，本科 ➢ 获得奖励: 2012 年获山东农业大学优秀毕业论文奖 2016 年获京津冀青年概率统计学术会议钟家庆优秀论文奖 2016 年中国科学院院长优秀奖学金研究项目 (1) 上海市纳税风险识别模型技术研究(横向)，2015年; (2) 带信息的纵向数据统计建模及其应用, 中央高校基本科研业务费 (Grant Nos. 20205170465), 2017-2018. 联系地址：湖北武汉市洪山区城区珞喻路152号，430079.

研究领域

生存分析,复发事件及纵向数据分析非参数统计高维数据分析精准医疗

近期论文

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➢Accepted/Revised/Submitted： (1) Lianqiang Qu, Xinyuan Song and Liuquan Sun, (2018). Identification of local sparsity and variable selection for additive hazard model with varying coefficients. Computational Statistics & Data Analysis, 125, 119-135; (2) Ting Yan, Lianqiang Qu, Zhaohai, Li and Ao Yuan, (2018). Conditional kernel density estimation for some incomplete data models. Electronic Journal of Statistics, 12, 1299–1329; (3) Lianqiang Qu, Liuquan Sun and Xinyuan Song, (2018). A joint modeling approach for longitudinal data with informative observation times and a terminal event. Statistics in Biosciences: 10, 609–633. (4) Lianqiang Qu, Liuquan Sun and Lei Liu, (2017). Joint modeling of recurrent event data with a dependent terminal event. Statistics and Its Interface: 10, 699–710; (5) Hu Zhang, Qinglong Yang and Lianqiang Qu, (2016). A class of transformation rate models for recurrent event data. Science China Mathematics: 59, 2227-2244; (6) Lianqiang Qu and Liuquan Sun, The Cox-Aalen model for recurrent event data with a dependent terminal event. (accepted). (7) Lianqiang Qu and Liuquan Sun. A non-marginal variable screening method for varying coefficient Cox model. (submitted) (8) Dongxiao, Han, Lianqiang, Qu, Liuquan, Sun, Yanqing, Sun. Variable selection for the mark-specific additive hazards model using the adaptive Lasso. (submitted) (9) Dongxiao, Han, Meiling Hao, Lianqiang, Qu and Wei Xu. A novel model for the X-chromosome inactivation association on survival data.(submitted) ➢ Manuscript: (1) Lianqiang Qu and Liuquan Sun. Variable screening for varying coeﬃcient single index models with ultrahigh dimensional survival data. (2) Lianqiang Qu. Non-marginal screening via sparsity-restricted estimating equation for high dimensional competing risks data. (3) Peng Ye, Lianqiang Qu, Liuquan Sun, Xingqiu Zhao and Wei Xu. Nonparametric estimation of marginal additive rates model for multivariate recurrent events with missing event category. (4) Peng Ye, Lianqiang Qu, Jie Zhou and Liuquan Sun. A semiparametric additive hazards model for multivariate gap time data. (5) Lianqiang Qu, Meiling Hao, Dongxiao Han and Liuquan Sun. Generalized test statistics for subgroup analysis. ➢ 中文论文 (1) 曹学峰，曲连强*, (2017), 带信息终止事件的复发事件数据的联合建模分析. 应用数学学报, 40 (4), 530-542; (2) 孙琴，曲连强*，(2018), 带相依终止事件的复发事件数据的可加可乘比率模型. 数学学报, Accepted ;