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Latent Variable Models and Methods

Latent Variable Models and Methods
潜变量模型和方法
批准号:
7046844
负责人:
Melanie M Wall
金额:
$18.44万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-04-01 至 2008-03-31

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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.
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Core B: Statistical and Computational Analysis Core
OPAL Center Methods Core
Multilevel latent class and social network models for observational adolescent ob
Multilevel latent class and social network models for observational adolescent ob
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