Measurement Models in Latent Curve Analysis

描述（由申请人提供）：在我们的第一个项目期间，我们专注于纵向潜在曲线模型（lcm）的系统研究，该模型应用于连续量表得分，特别强调在物质使用的实证研究中通常出现的挑战。尽管这些lcm有许多优点，但一个限制是，目前还没有很好地开发方法来使lcm适合于常规尺度的重复测量，特别是在存在缺失数据的情况下。第二个限制源于可能违反一组严格的必要假设，这些假设控制着随时间连续或顺序观察的尺度分数的测量模型的结构。为了解决这些局限性，我们借鉴了最初项目期间的研究结果，并围绕潜在曲线分析中测量模型的系统研究设计了我们拟议的后续项目的修订。我们提出的项目是围绕四个具体目标组织的。在目标1中，我们建议研究现有的挑战，并确定将lcm拟合到具有完整和缺失数据的有序清单量表分数的最佳策略。在目标2中，我们计划在lcm中研究潜在因素与连续尺度指标的结合，以允许测试测量不变性和包含正式测量模型。在目标3中，我们建议扩展目标2的研究结果，包括将潜在因素与lcm中按顺序缩放的指标相结合。最后，在目标4中，我们计划研究项目量表和测量不变性在所有先前目标中对统计能力估计和最佳研究设计的影响。这些项目目标将通过综合使用分析性审查和组织、计算机模拟研究和分析从现有的一项关于父母酗酒对大量青少年吸毒发展的影响的纵向研究中获得的数据来实现。综上所述，我们认为拟议的研究有可能对定量方法领域和对药物使用和滥用的发展轨迹进行严格的实证研究作出重大的独特贡献。

DESCRIPTION (provided by applicant): In our first project period we focused on the systematic study of longitudinal latent curve models (LCMs) applied to continuous scale scores with a particular emphasis on challenges that commonly arise in the empirical study of substance use. Despite the many advantages of these LCMs, one limitation is that methods are currently not well developed to fit LCMs to repeated measures that are ordinally scaled, particularly in the presence of missing data. A second limitation stems from the potential violation of a strict set of required assumptions governing the structure of the measurement model of continuous or ordinally observed scale scores over time. To address these limitations, we have drawn upon our findings from the initial project period and have designed the revision of our proposed continuation project around the systematic study of measurement models in latent curve analysis. Our proposed project is organized around four specific aims. In Aim 1 we propose to study existing challenges and identify optimal strategies for fitting LCMs to ordinal manifest scale scores assessed overtime both with complete and missing data. In Aim 2 we plan to study the incorporation of latent factors with continuously scaled indicators in LCMs to allow for tests of measurement invariance and the inclusion of formal measurement models. In Aim 3 we propose extending the findings of Aim 2 to include the incorporation of latent factors with ordinally scaled indicators in LCMs. Finally, in Aim 4 we plan to study the implications of item scaling and measurement invariance across all prior aims with respect to the estimation of statistical power and optimal study design. These project goals will be pursued through the integrated use of analytical review and organization, computer simulation studies, and the analysis of data drawn from an existing longitudinal study of the parental alcoholism effects on the development of drug use in a large sample of adolescent. Taken together, we believe the proposed study has the potential for making significant unique contributions to the field of quantitative methodology and to the rigorous empirical study of developmental trajectories of substance use and abuse.