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New Statistical Methodology to Establish Construct Validity for Childhook Risk

建立童年风险构建有效性的新统计方法

基本信息

批准号：
8451448
负责人：
Yuh-Pey Anne Buu
金额：
$ 14.29万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-04-10 至 2014-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8451448
关键词：
Accounting Adolescence Adolescent Adult Alcohol abuse Alcohol consumption Alcohol or Other Drugs use Alcoholism Alcohols Area Behavior Child Childhood Computational Technique Data Development Dimensions Dose Early Intervention Epidemiology Evaluation Evaluation Research Family Functional disorder Health Health Benefit Illicit Drugs Impairment Individual Individual Differences Long-Term Effects Longitudinal Studies Measurement Measures Mental disorders Mentored Research Scientist Development Award Methodology Methods Michigan Modeling Nature Pharmaceutical Preparations Predictive Value Prevention Prevention Research Probability Property Prospective Studies Psychopathology Public Health Reporting Research Research Design Research Institute Research Methodology Risk Risk Assessment Risk Estimate Role Scientist Statistical Methods Statistical Models Suicide attempt Surveys Testing Time Training Work Youth adolescent substance use alcohol use disorder base binge drinking career career development cost design direct application drinking early childhood high risk high risk sexual behavior neuropsychological programs social statistics substance abuse prevention success theories tool trait

项目摘要

DESCRIPTION (provided by applicant): This Mentored Research Scientist Development Award will support the candidate in establishing an independent research career as a methodologist who develops cutting-edge statistical methodology with direct applications in alcoholism and substance abuse prevention. Career development training areas include: 1) Development psychopathology; 2) Alcoholism and substance abuse prevention research and methodology; 3) Modern computational techniques; and 4) Modeling longitudinal data using nonparametric regression. The specific aims of the proposed research plan are: 1) To develop a new Bayesian latent variable model for assessing dynamic childhood risk for alcoholism in multiple dimensions; 2) To develop a new semi-parametric regression model for validating the association between childhood risk and adolescent substance use development; and 3) To apply the methodologies developed in Specific Aims 1 and 2 to test hypotheses based on the data collected from an ongoing 21-year long prospective study of families at high risk for alcoholism. The methodology developed in this study will be useful in establishing construct validity of commonly used measures of childhood risk. Two statistical programs will be developed and distributed to prevention scientists. The derived longitudinal model based on the empirical data should be useful in projecting a new child's developmental trajectory of adolescent substance use based on his/her childhood risk measures. Thus, it has the potential to provide crucial information about the timing and dose an individual child needs for early intervention.

该指导研究科学家发展奖将支持候选人建立独立的研究职业生涯，作为一名方法学家，他开发了直接应用于酗酒和药物滥用预防的尖端统计方法。职业发展培训领域包括：1）发展精神病理学; 2）酗酒和药物滥用预防研究和方法; 3）现代计算技术;和4）使用非参数回归建模纵向数据。研究计划的具体目标是：1）开发一个新的贝叶斯潜变量模型，用于多维度评估儿童期酒精中毒的动态风险; 2）开发一个新的半参数回归模型，用于验证儿童期风险与青少年物质使用发展之间的关联;以及3）应用具体目标1和2中开发的方法来检验基于从正在进行的21年长期酗酒高危家庭前瞻性研究中收集的数据的假设。在这项研究中开发的方法将是有用的，在建立结构效度的常用措施的儿童风险。将制定两个统计方案并分发给预防科学家。根据经验数据推导的纵向模型应该是有用的，在预测一个新的儿童的发展轨迹的青少年物质使用的基础上，他/她的童年风险措施。因此，它有可能提供有关个别儿童需要早期干预的时间和剂量的关键信息。