Extensions and Applications of Group-Based Models of Development and the Software for Estimating Them

基于群体的发展模型及其评估软件的扩展和应用

• 批准号: 0647576
• 负责人: Daniel Nagin
• 金额: --
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0647576&HistoricalAwards=false
• 关键词: Extensions; Applications; Group; Based; Models

A developmental trajectory describes the course of a behavior over age or time. This project builds upon prior NSF-funded research (SES-9911370 & SES-9511412) that developed a group-based approach for identifying distinctive groups of individual trajectories within the population of interest. As part of that research, "canned" SAS-based software (Proc Traj), distributed free of charge, was developed for estimation of the trajectory models. This project will address three major issues. First, all longitudinal studies, particularly of people, suffer from the problem of missing assessments because subjects drop out of the study for reasons such as death or because they can not be located or are no longer willing to participate. Because subject drop-out is not random, one important objective of the research is to extend the basic model to account for differential drop-out rates by trajectory group. This enhancement will be incorporated into the Proc Traj software. Second, prior work links group-based trajectory modeling with work on propensity scores and matching. The aim of this linkage is to make (more confident) causal inferences about the effect of major life events or therapeutic interventions on trajectories of behavior. The posterior probabilities of group membership, a key product of group-based trajectory modeling, play a central role in linking these two lines of research. A second important objective of the research is to explore the contribution of the posterior probabilities in creating balance on measured covariates between treated and controls. Third, for reasons of tractability, trajectory models estimated with Proc Traj assume conditional independence across time periods within trajectory group. This research also will explore the impact of this assumption's failure on parameter estimates and their standard errors. The methodological extensions will be used to investigate important substantive questions in developmental psychopathology and developmental criminology. In this regard, the work on causal inference has an important application domain in assessing the effectiveness of nonrandomly assigned medical treatments, including psychiatric counseling and drug treatment, and in analyzing the impact of events such as incarceration on subsequent criminality. Application of the extension to account for non-random drop-out may reveal important biases in findings that do not take this phenomenon into account. Also, wide dissemination of Proc Traj free of charge allows other researchers to more easily utilize the methodological advances of this research. It is important to note that many Ph.D. candidates and postdoctoral scholars use Proc Traj. Thus, this research contributes to the education of the next generation of researchers.

发展轨迹描述了一种行为随着年龄或时间的变化过程。该项目建立在先前由国家科学基金会资助的研究(SES-9911370和SES-9511412)的基础上，该研究开发了一种基于群体的方法来识别感兴趣人群中独特的个人轨迹组。作为这项研究的一部分，为估计弹道模型，开发了免费分发的“罐装”基于SAS的软件(Proc Traj)。这个项目将解决三个主要问题。首先，所有纵向研究，特别是对人的纵向研究，都存在评估缺失的问题，因为受试者因死亡等原因退出研究，或者因为无法找到他们或不再愿意参与。由于受试者退学不是随机的，本研究的一个重要目的是扩展基本模型，以解释不同轨迹组的退学率差异。这一增强功能将合并到proc traj软件中。第二，以前的工作将基于群体的弹道建模与倾向得分和匹配工作联系起来。这种联系的目的是对重大生活事件或治疗干预对行为轨迹的影响做出(更有信心的)因果推断。群体成员的后验概率是基于群体的轨迹建模的关键产品，在连接这两条研究路线中起着核心作用。这项研究的第二个重要目标是探索后验概率对在治疗组和对照组之间测量的协变量之间创造平衡的贡献。第三，出于易于处理的原因，用PROC TRAJ估计的轨迹模型假定在轨迹组内跨时间段有条件地独立。这项研究还将探讨这一假设的失败对参数估计及其标准误差的影响。方法论的延伸将被用于研究发展精神病理学和发展犯罪学中的重要实质性问题。在这方面，因果推断的工作在评估非随机分配的医疗，包括精神咨询和药物治疗的有效性以及分析监禁等事件对后续犯罪行为的影响方面具有重要的应用领域。应用扩展来解释非随机辍学可能会揭示没有考虑到这一现象的研究结果中的重大偏见。此外，免费广泛传播proc traj允许其他研究人员更容易地利用这项研究的方法学进步。值得注意的是，许多博士生和博士后学者使用proc traj。因此，本研究有助于下一代研究者的教育。