System-subsystem modeling with an application to disability in older adults

描述(由申请人提供)：该项目旨在探索一种新的方法，称为系统-子系统依赖网络，用于建模大型、复杂的系统。这项先导性研究的主要动机是将系统分析应用于老年人残疾的研究。与社会和行为科学的许多其他系统方法一样，残疾的建模涉及不同的数据来源，如试点实验、流行病学和临床研究、人口普查数据和监测系统。它还涉及多个子系统--一个系统中的组件，它们在结构和功能上都是相互衔接的。虽然子系统在整个系统上提供了外部和隐性知识的有意义的覆盖，但它们往往必须使用不同的数据源和不同的数据集进行单独校准。方法学上的一个挑战是协调重叠的子系统以及各个单独校准的子系统之间潜在的参数不一致。该项目扩展了一种灵活的工具--广义依赖网络--来解决这些问题。通过仿真实验，对实现系统-子系统依赖网络的计算工具进行了测试。除了探索使用广义依赖网络实现系统-子系统方法的核心思想外，该试点项目还使用两项关于老龄化的研究数据，对简化的残疾模型的适用性进行了实证检验，该模型仅限于物理和认知子系统。

DESCRIPTION (provided by applicant): The project aims to explore a novel approach, called system-subsystem dependency network, for modeling large, complex systems. This pilot study is primarily motivated by an application of system analysis to the study of disablement in older adults. Like many other system approaches to social and behavioral sciences, the modeling of disablement involves diverse data sources such as pilot experiments, epidemiologic and clinical studies, census data, and surveillance systems. It also involves multiple subsystems - components within a system that are individually cohesive both in structures and functions. While subsystem provides a meaningful overlay of external and tacit knowledge over the entire system, they often have to be individually calibrated using diverse data sources and different data sets. A methodological challenge is to reconcile overlapping subsystems as well as the potential parametric inconsistency across individually calibrated subsystems. The project extends a flexible tool - the generalized dependency network - for solving such problems. Through simulation experiments, state-of-the-art computational tools are tested for implementing the system- subsystem dependency network. Besides exploring the key idea of using generalized dependency network for operationalizing the system-subsystem approach, this pilot project also empirically tests the applicability of the method to a simplified disablemet model, which is restricted to the physical and cognitive subsystems, using data from two studies of aging.