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，我们专注于纵向潜伏曲线模型（LCM）应用于连续量表分数的系统研究，特别强调物质使用实证研究中常见的挑战。尽管这些LCM有许多优点，但一个局限性是，目前还没有很好地开发出将LCM拟合到按顺序缩放的重复测量的方法，特别是在存在缺失数据的情况下。第二个限制源于潜在的违反一组严格的必要的假设，管理结构的测量模型的连续或定期观察的量表分数随着时间的推移。为了解决这些局限性，我们借鉴了我们在项目初期的发现，并围绕潜在曲线分析中测量模型的系统研究，设计了我们拟议的继续项目的修订。我们的项目围绕四个具体目标展开。在目标1中，我们建议研究现有的挑战，并确定最佳策略，以拟合LCM，以有序的显式量表评分评估超时完整和缺失的数据。在目标2中，我们计划研究在LCM中将潜在因素与连续缩放的指标结合起来，以允许测试测量不变性和纳入正式的测量模型。在目标3中，我们建议扩展目标2的研究结果，以包括将潜在因素与LCM中的按顺序缩放的指标相结合。最后，在目标4中，我们计划研究项目缩放和测量不变性对统计功效估计和最佳研究设计的影响。这些项目的目标将通过综合利用分析性审查和组织、计算机模拟研究以及分析从一项关于父母酗酒对青少年大样本吸毒发展的影响的现有纵向研究中得出的数据来实现。综上所述，我们认为，拟议的研究有可能作出重大的独特贡献的定量方法和严格的实证研究的发展轨迹的物质使用和滥用的领域。

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.