Dynamic Modeling of Recurrent Events and Its Applications

重复事件的动态建模及其应用

• 批准号: 1915829
• 负责人: Yanqing Sun
• 金额: $ 13.99万
• 依托单位: University of North Carolina at Charlotte
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1915829&HistoricalAwards=false
• 关键词: Dynamic; Modeling; Recurrent; Events; Its

This project will develop some novel statistical methods for the recurrent events. The proposed research is motivated by the need to develop new statistical methodology for the malaria vaccine trial and other biometrical researches. The proposed statistical methods can be used to assess the risk factors of event occurrences, how the occurrences of events and event types are affected by concomitant variables, intervention, the past history, as well as the associations among different types of events. The proposed research is challenging in theoretical development and in statistical computation. The proposed statistical methods can facilitate the analysis of the malaria vaccine trial and contribute to develop efficacious malaria vaccines toward control and elimination of malaria. The development of the outlined research would enrich a collection of statistical tools for understanding the event histories and contribute to the efforts to overcome the medical and public health challenges and beyond. The graduate student support will be used for research on the theory of malaria control. The research aims to develop nonparametric and semiparametric dynamic models for the recurrent events that will advance the existing statistical methods for recurrent events. The statistical methods are proposed to model and assess the risk factors of event occurrences, how the occurrences of events and event types are affected by concomitant variables, interventions, and the event history. New statistical methods also proposed to investigate the associations among different types of events. The proposed research is motivated by the challenges arising from analyzing the malaria vaccine efficacy trialand has broach applications in other fields such as biomedical, reliability and economics. The proposed research includes two parts. The research for the dynamic varying-coefficient intensity models of event occurrences is described in Part I which introduces three models: the nonparametric dynamic varying-coefficient intensity model, the semiparametric dynamic varying-coefficient intensity model, and the dynamic models for multiple type of recurrent events. Research for modeling and assessing the associations among different types of recurrent events is proposed in Part II. The nonparametric dynamic varying-coefficient intensity models will be estimated based on the likelihood principle and the local linear smoothing technique. The profile estimation approach will be utilized for the semiparametric dynamic varying-coefficient intensity models. The inference procedures that are of scientific interest will be investigated. Large sample theory will be developed for the proposed estimation and hypothesis testing procedures. A two-stage estimating procedure is proposed to estimate the models for the conditional rate function of the recurrent event processes where the marginal semiparametric models are estimated in the first stage and the models for the rate ratio are estimated in the second stage. Studies are proposed to investigate a variety of models for the conditional rate ratio. New statistical methods, theory and computational algorithms will be developed. The proposed statistical methods can facilitate the analysis of the malaria vaccine trial and contribute to develop efficacious malaria vaccines toward control and elimination of malaria.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

本计画将发展一些新的统计方法来分析复发事件。提出的研究的动机是需要开发新的统计方法的疟疾疫苗试验和其他生物统计学研究。所提出的统计方法可用于评估事件发生的风险因素，事件和事件类型的发生如何受到伴随变量、干预、既往史以及不同类型事件之间的关联的影响。所提出的研究在理论发展和统计计算方面具有挑战性。所提出的统计方法可以方便地分析疟疾疫苗试验，并有助于开发有效的疟疾疫苗，以控制和消除疟疾。概述的研究的发展将丰富一系列统计工具，以了解事件的历史，并有助于克服医疗和公共卫生挑战及其他方面的努力。 研究生资助将用于疟疾控制理论研究。 本研究的目的是建立复发事件的非参数和半参数动态模型，以改进现有的复发事件统计方法。提出了统计方法来建模和评估事件发生的风险因素，事件的发生和事件类型如何受到伴随变量，干预措施和事件历史的影响。新的统计方法也被提出来研究不同类型事件之间的关联。 这项研究的动机是分析疟疾疫苗有效性试验所带来的挑战，并在生物医学、可靠性和经济学等其他领域得到了应用。 本研究包括两个部分。 第一部分是事件发生的动态变系数强度模型的研究，主要介绍了三种模型：非参数动态变系数强度模型、半参数动态变系数强度模型和多类复发事件的动态模型。在第二部分中提出了建模和评估不同类型的复发事件之间的关联的研究。基于似然原理和局部线性平滑技术对非参数动态变系数烈度模型进行估计。轮廓估计方法将用于半参数动态变系数强度模型。将研究具有科学意义的推理程序。大样本理论将发展为拟议的估计和假设检验程序。本文提出了一种两阶段估计方法来估计复发事件过程的条件率函数模型，第一阶段估计边际半参数模型，第二阶段估计率比模型。研究提出了各种模型的条件率比。将开发新的统计方法、理论和计算算法。建议的统计方法可以促进疟疾疫苗试验的分析，并有助于开发有效的疟疾疫苗，以控制和消除疟疾。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Neutralizing antibody correlates of sequence specific dengue disease in a tetravalent dengue vaccine efficacy trial in Asia

在亚洲进行的四价登革热疫苗功效试验中，中和抗体与序列特异性登革热疾病相关

• 发表时间: 2022
• 期刊: Vaccine
• 影响因子: 5.5
• 作者: Qi, Li;Sun, Yanqing;Juraska, Michal;Moodie, Zoe;Magaret, Craig A;Heng, Fei;Carpp, Lindsay N;Gilbert, Peter B.
• 通讯作者: Gilbert, Peter B.

Analysis of the time-varying Cox model for the cause-specific hazard functions with missing causes

缺失原因的特定原因危险函数的时变 Cox 模型分析

• DOI: 10.1007/s10985-020-09497-y
• 发表时间: 2020
• 期刊: Lifetime Data Analysis
• 影响因子: 1.3
• 作者: Heng, Fei;Sun, Yanqing;Hyun, Seunggeun;Gilbert, Peter B.
• 通讯作者: Gilbert, Peter B.

A mark-specific quantile regression model

• DOI: 10.1093/biomet/asad039
• 发表时间: 2023-07-31
• 期刊: BIOMETRIKA
• 影响因子: 2.7
• 作者: Qu，Lianqiang;Sun，Liuquan;Sun，Yanqing
• 通讯作者: Sun，Yanqing

Semiparametric regression analysis of partly interval-censored failure time data with application to an AIDS clinical trial.

• DOI: 10.1002/sim.9035
• 发表时间: 2021-09-10
• 期刊: STATISTICS IN MEDICINE
• 影响因子: 2
• 作者: Zhou, Qingning;Sun, Yanqing;Gilbert, Peter B.
• 通讯作者: Gilbert, Peter B.

Analysis of the Cox Model with Longitudinal Covariates with Measurement Errors and Partly Interval Censored Failure Times, with Application to an AIDS Clinical Trial.

• DOI: 10.1007/s12561-023-09372-y
• 发表时间: 2023
• 期刊: STATISTICS IN BIOSCIENCES
• 影响因子: 1
• 作者: Sun, Yanqing;Zhou, Qingning;Gilbert, Peter B
• 通讯作者: Gilbert, Peter B