Latent Variable Models and Methods

描述（由申请人提供）：潜在变量是指不能直接观察到的现象，而必须通过一系列问题或项目检查表来测量。抑郁症、饮食失调、家庭联系和严重的酒精问题就是一些例子。这个建议是为潜在变量开发新的方法和模型（具体目标如下），可以非常普遍地应用。这些方法的有用性将通过来自公共卫生行为健康研究项目的两组现有数据来证明。这两个项目在主题和数据收集方面有很大的不同，但共同之处在于，都需要对不能直接观察到的概念现象的变量（即潜在变量）进行建模。第一个研究项目涉及对明尼苏达州4746名青少年进行221项调查，评估一系列与所测结果潜在相关的社会环境、个人和行为因素，包括营养健康、肥胖和危害健康的行为，如吸毒和酗酒。第二个研究项目从保险索赔的管理数据库中收集了一个数据集，其中包括32985名在1993年至2000年间被诊断患有酒精问题的成年人。该纵向数据库还与一份社会心理问卷相关联，该问卷对5683名接受酒精中毒治疗的患者进行了调查。具体目标是：1。为了弥合分类潜变量和连续潜变量模型之间的差距，特别关注连续潜变量和分类潜变量之间的结构关系建模。开发连续潜变量和分类潜变量之间非线性关系的建模方法。发展用连续和分类潜变量模型建模多变量纵向数据的方法。最后，本提案的总体目标是使用开发的方法和模型来回答与青少年健康损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.