Health & Other Predictors of Expected & Actual Mobility

NIA试点研究资助计划。优先领域24：改进措施和方法。 退休后的居住流动性部分是由健康驱动的。积极的健康状况促进退休初期的流动性，消极的健康状况促进退休后期的流动性。这个项目的核心问题是发现如何预测一个移动的预期为晚临退休和提前退休后搬家的实际移动。迁移决策的行为模型指导着我们的工作。我们的期望，关于我们的具体目标，是：具体目标一：确定1）资源变量，包括货币资源，2）旅行经验，3）社区关系在原产地，流动性，预期和实际之间的关系的性质。具体目标2：确定旅行经验与预期和实际流动可能性之间关系的性质。具体目标3：确定社区联系与预期或实际流动可能性之间关系的性质。具体目标4：确定预期流动与实际流动之间关系的性质。具体目标5：确定预测流动性的变量的净效应是否取决于性别、劳动力状况或种族/民族 背景 该研究将使用健康与退休研究（HRS）的数据。1992年的数据浪潮 包含对资源、旅行经验、社区联系和预期流动性的衡量。1992年至1994年期间的实际流动情况可从人力资源调查第二波中得到。拟议分析的核心将采用多项和二项逻辑回归，以分别对预期流动性和实际流动性进行建模。此外，拟议的分析设计（1）考虑了HRS使用的复杂抽样设计所产生的统计问题，并利用SUDAAN软件，（2）试图探索可能影响移动行为和态度的夫妇水平动态。具体的期望是 阐述了关键预测变量之间的关系和建模策略，以评估这些期望。

NIA Pilot Research Grant Program. Priority Area 24: Improved Measures and Methodologies. Residential mobility in retirement is partly driven by health. Positive health status promotes mobility early in retirement, and negative health status later in retirement. The central concern of this project is to discover how well expectations of a move predict an actual move for late pro-retirement and early post-retirement movers. A behavioral model of migration decision-making guides our effort. Our expectations, with regard to our specific aims, are: Specific Aim I: To determine the nature of the relationship between 1) resource variables, including and monetary resources, 2) travel experience, and 3) community ties at origin, and mobility, both expected and actual. Specific Aim 2: To determine the nature of the relationship between travel experience and the likelihood of mobility, both expected and actual. Specific Aim 3: To determine the nature of the relationship between community ties and the likelihood of mobility, both expected or actual. Specific Aim 4: To determine the nature of the relationship between expected mobility and actual mobility. Specific Aim 5: To determine whether the net effect of variables predicting mobility depend upon gender, labor force status, or race/ethnic background. The study will use data from the Health and Retirement Study (HRS). The 1992 wave of the data contains measures of resources, travel experience, community ties, and expected mobility. A measure of actual mobility between 1992 and 1994 is available from the second wave of the HRS. The core of the proposed analysis will employ multinomial and binomial logistic regression in order to model expected mobility and actual mobility respectively. Additionally the proposed analytical design (1) accounts for statistical issues arising from the complex sampling design used by the HRS by making use of SUDAAN software and (2) seeks to explore couple-level dynamics that may shape mobility behavior and attitudes. Specific expectations are articulated with respect to the relationships between and among key predictor variables and a modeling strategy to evaluate these expectations is delineated.