RANDOM EFFECT MODELS FOR SUBSTANCE ABUSE RESEARCH

药物滥用研究的随机效应模型

• 批准号: 2733555
• 负责人: CHIH-PING CHOU
• 金额: $ 17.08万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-07-01 至 2000-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2733555
• 关键词: adolescence (12-20); behavioral /social science research tag; human data; mathematical model; model design /development; psychological models; substance abuse epidemiology; substance abuse related disorder

DESCRIPTION: (Applicant's Abstract) This is for secondary data analysis that will apply and test a state-of-the-art multilevel statistical approach to research on the prevention of substance abuse. The analytical technique to be tested, the random-effect model (REM) allows simultaneous processing of information from different levels (e.g., student, class, school, etc.). Conventional approaches with single-level analyses and conventional multilevel models contain shortcomings in specifying substantive models or in statistical testing of hypotheses, which in turn may lead to unreliable results and erroneous conclusions. The REM provides a more appropriate mechanism to represent the complexity of the multilevel data and a more adequate model specification to test the impact of social contexts. The ability to test contextual effects makes the application of REM a very promising alternative for data analyses in substance abuse research. Having the flexibility to model random group effects, the REM also offers a more powerful alternative to examine the impact of social context on substance use. The extension of this approach to substance abuse research may help us understand more about the impact of prevention programs. In this proposed project, hierarchical linear models will be developed and applied to data from a substance abuse prevention study to identify important contextual and individual effects on substance use. Results obtained from the REM will be compared to that of other conventional multilevel approaches. In addition, the issues of robustness to violations of normal distribution and sensitivity to the number of groups of the REM will be investigated. Other potential methodological concerns, such as dichotomized outcome, latent factor, and survival analysis, will also be examined. Findings from this project should provide guidelines for appropriate REM application, a better understanding of the contribution of environmental contexts to effects of prevention programs, and more valid estimation of program effects on substance abuse.

描述：（申请人的摘要） 这是针对辅助数据分析，该分析将应用和测试 最先进的多层次统计方法研究 预防药物滥用。 要测试的分析技术， 随机效应模型（REM）允许同时处理信息 不同的级别（例如，学生，班级，学校等）。传统的 单层分析和常规多级模型的方法 包含指定实体模型或统计中的缺点 测试假设，这又可能导致不可靠的结果和 错误的结论。 REM提供了更合适的机制 表示多级数据的复杂性和更适当的模型 测试社会环境影响的规范。 测试能力 上下文效果使REM的应用成为非常有前途的替代方案 用于药物滥用研究的数据分析。 具有灵活性 模型随机组效应，REM还提供了更强大的替代方案 检查社会环境对物质使用的影响。 扩展 这种滥用药物研究的方法可能会帮助我们更多地了解 预防计划的影响。 在这个拟议的项目中，将开发层次线性模型，并 应用于预防滥用药物的数据以识别 重要的上下文和个人对使用物质的影响。 结果 将从REM获得的其他常规 多级方法。 此外，违规的鲁棒性问题 对REM组数量的正态分布和敏感性 将被调查。 其他潜在的方法论问题，例如 二分法的结果，潜在因素和生存分析也将是 检查。 该项目的发现应为 适当的REM应用，更好地理解 环境环境预防计划的影响，更有效 估计程序对药物滥用的影响。