Latent Variable Models and Methods

描述（由申请人提供）：潜在变量是无法直接观察到的现象，而是必须使用一些问题或项目检查表进行测量。抑郁症、饮食失调、家庭联系和酒精问题的严重性就是一些例子。该提案旨在为潜在变量开发新的方法和模型（具体目标见下文），这些方法和模型可以非常普遍地应用。这些方法的有用性将显示与两个现有的数据集来自公共卫生行为健康研究项目。这两个项目在主题和数据收集方面有很大不同，但共同点是需要对由于其概念现象性质而无法直接观察到的变量（即潜在变量）进行建模。第一个研究项目涉及明尼苏达州4746名青少年的221项调查，评估一系列与测量结果潜在相关的社会环境，个人和行为因素，包括营养健康，肥胖和健康危害行为，如药物和酒精使用。第二个研究项目从保险索赔的行政数据库中收集了1993-2000年期间被诊断有酒精问题的32，985名成年人的数据集。这一纵向数据库还与一个心理社会问卷调查，管理到一个子集的5683例患者在他们提出的酗酒治疗。具体目标是1.为了弥合分类和连续潜变量模型之间的差距，特别注意对连续和分类潜变量之间的结构关系进行建模2。开发连续和分类潜变量之间的非线性关系建模方法3.发展连续潜变量模型和分类潜变量模型对多变量纵向数据建模的方法。本提案的最后一个总体目标是使用开发的方法和模型来回答与青少年健康危害行为和成年酗酒者医疗结果等特定领域的公共卫生相关的研究问题。

DESCRIPTION (provided by applicant): Latent variables are phenomena that cannot be observed directly and instead must be measured using, for example, some battery of questions or check list of items. Depression, eating disorders, family connectedness and severity of alcohol problems are some examples. This proposal is to develop new methods and models for latent variables (specific aims below) that can be applied very generally. The usefulness of these methods will be shown with two existing data sets originating from behavioral health research projects in public health. The two projects are very different in subject matter and data collection, but share in common the need to model variables that because of their nature as conceptual phenomena cannot be observed directly (i.e. latent variables). The first research project involves a 221-item survey of 4746 adolescents in Minnesota assessing a range of socio-environmental, personal, and behavioral factors of potential relevance to the outcomes measured, including nutritional health, obesity, and health compromising behaviors such as drug and alcohol use. The second research project assembled a dataset from an administrative database of insurance claims for 32,985 adults diagnosed to have had an alcohol problem between 1993-2000. This longitudinal database is also linked with a psychosocial questionnaire administered to a subset of 5683 patients at the time they presented for alcoholism treatment. The specific aims are 1. To bridge the gap between categorical and continuous latent variable models with specific attention put on modeling the structural relationship between continuous and categorical latent variables 2. To develop methods for modeling nonlinear relationships between both continuous and categorical latent variables 3. To develop methods for modeling multivariate longitudinal data with both continuous and categorical latent variable models. A final, overarching aim of this proposal is to use the methods and models developed to answer research questions relevant for public health in the specific areas of adolescent health compromising behavior, and medical outcomes for adult alcoholics.