Data Management, Measurement and Statistical

数据管理、测量和统计核心(DMMS)将侧重于四个目标：(1)提供 最先进的数据管理和统计资源以及跨项目的支持；(2)开发 跨项目使用常用的心理测量学合理测量方法，特别是吸烟行为测量方法 和成果；(3)实施跨项目、综合分析；(4)发展统计技术 以及解决与青少年吸烟数据分析有关的关键问题的方法。 (一)支撑。将维持一个包含所有纵向研究数据的计算机化数据库 从EMA表格、结构化访谈、青少年和家长问卷、学校和 生理测量。将实施严格的数据输入、编辑和更新方法，以 确保数据干净、一致和安全。数据库的详细文档将在 由这个核心开发出来的。将为所有项目提供统计支持和协作。 (2)测量。该计划项目的目的是增加对 青少年吸烟及其发生的情感和社会背景。DMM的核心目标是 概念化并制定措施，以：(A)确定纵向吸烟模式的特征；(B) 在分析这些模式发展的背景时易于处理和解释。 (3)一体化。该方案项目的一个主要特点是，将从主要研究中获得数据 队列(七波)和三个项目。在数字模型中，统计模型的发展允许 对来自多个来源的数据进行综合分析将是一个主要优先事项。这个v，将使用 各种先进的统计方法。目的是为了更全面地了解青少年 吸烟比通过单独分析数据可以获得的数据更多。 (4)发展。DMMS核心内的方法学研究将寻求推动发展 用于分析吸烟数据的统计方法。这些努力将围绕以下几个方面展开 主要问题：“依赖”的多个指数的概念化/组合，个体 吸烟随时间发展的异质性，吸烟预测因素影响的异质性， 并描述了吸烟依赖的各个阶段。

The Data Management, Measurement, and Statistics core (DMMS) will focus on four aims: (1) to provide state-of-the-art data management and statistical resources and support across projects; (2) to develop common, psychometrical-ty sound measures to use across projects, notably measures of smoking behaviors and outcomes; (3) to implement cross-project, integrated analyses; and (4) to develop statistical techniques and approaches to address key issues related to the analysis of adolescent smoking data. ( 1) SUPPORT. A computerized database will be maintained containing all longitudinal reseamh data obtained from EMA forms, structured interviews, adolescent and parent questionnaires, schools, and physiological measurements. Rigorous methods for data entry, editing, and updating will be implemented to ensure that the data are clean, consistent, and secure. Detailed documentation of the database will be developed by this core. Statistical support and collaboration for all projects will be provided. (2) MEASUREMENT. The program project aims to increase understanding of the longitudinal patterns of adolescent smoking and the emotional and social contexts in which these occur. A DMMS core aim is to conceptualize and develop measures that will: (a) characterize longitudinal smoking patterns and (b) be tractable and interpretable in the analysis of the contexts in which these patterns develop. (3) INTEGRATION. A key feature of the program project is that data will be available from the main study cohort (seven waves) and the three projects. In the DMMS, development of statistical models that allow integrated analyses of data from many sources will be a major priority. This v, ill be accomplished using a variety of advanced statistical approaches. The goal is to obtain a more complete picture of adolescent smoking than could be obtained from analyzing the data separately. (4) DEVELOPMENT. Methodological research within the DMMS core will seek to advance development of statistical approaches for the analysis of smoking data. These efforts will be focused around the following primary issues: the conceptualization/combination of multiple indices of"dependence," individual heterogeneity in smoking development across time, heterogeneity in the influence of smoking predictors, and characterizing stages of smoking dependence.