Collaborative Research: Conditional Frailty Duration Model for the Study of Repeated Events in the Social Sciences

合作研究：社会科学研究重复事件的条件衰弱持续时间模型

• 批准号: 0647936
• 负责人: Janet Box-Steffensmeier
• 金额: $ 12.99万
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-04-15 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0647936&HistoricalAwards=false
• 关键词: Collaborative; Research; Conditional; Frailty; Duration

Repeated events processes, where a subject may experience the same type of event multiple times, are ubiquitous across a great range of important social science applications. The central aim of the research is to develop a robust estimation strategy for assessing covariate effects in repeated events survival models. As the center piece of that strategy, the conditional frailty model combines key features of alternative models designed to account for heterogeneity (a random effect) and for event dependence (stratification), with a conditional definition of the risk set in the same model. The goal of the research is to further test, extend, and apply the conditional frailty model.The research will advance the application of event history models and enable a deeper understanding of repeated events processes in the social sciences by developing survival estimators that accurately model heterogeneity and event dependence. More specifically, the research looks at the robustness of the conditional frailty model under complications introduced by a) varying degrees of censoring; b) small sample sizes; c) time dependence; and d) alternative forms of event dependence. The conditional frailty model will be extended to deal with a) multiple levels of analysis and b) competing risks. The conditional frailty model will be applied to two central social science questions: What explains the timing and occurrence of a) civil wars and b) the churning of children in foster care? Advances in the development and application of repeated events survival models will be widely applicable in the study of events in the social sciences. Additionally, the methodology will help practitioners in the public policy arena better assess the role of policies and conditions.

重复的事件过程，其中一个主体可能多次经历相同类型的事件，在大量重要的社会科学应用中无处不在。 本研究的主要目的是开发一种稳健的估计策略，用于评估重复事件生存模型中的协变量效应。 作为该策略的核心部分，条件脆弱性模型结合了旨在解释异质性（随机效应）和事件依赖性（分层）的替代模型的关键特征，并在同一模型中对风险集进行了条件定义。 本研究的目的是进一步检验、扩展和应用条件脆弱性模型，通过开发准确模拟异质性和事件依赖性的生存估计器，推进事件历史模型的应用，并使人们能够更深入地理解社会科学中的重复事件过程。 更具体地说，该研究着眼于条件脆弱性模型的鲁棒性下的并发症所引入的a）不同程度的删失; B）小样本量; c）时间依赖性;和d）事件依赖的替代形式。 条件脆弱性模型将被扩展以处理a）多层次分析和B）竞争风险。 条件性脆弱模型将被应用于两个中心的社会科学问题：如何解释a）内战和B）寄养儿童的搅动的时间和发生？ 重复事件生存模型的发展和应用将广泛应用于社会科学中的事件研究。 此外，该方法将帮助公共政策竞技场的从业人员更好地评估政策和条件的作用。