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Evaluating Interventions with Multimethod Data: A Structural Equation Modeling Approach

机译:用多方法数据评估干预:一种结构方程建模方法

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摘要

In many intervention and evaluation studies, outcome variables are assessed using a multimethod approach comparing multiple groups over time. In this article, we show how evaluation data obtained from a complex multitrait-multimethod-multioccasion-multigroup design can be analyzed with structural equation models. In particular, we show how the structural equation modeling approach can be used to (a) handle ordinal items as indicators, (b) test measurement invariance, and (c) test the means of the latent variables to examine treatment effects. We present an application to data from an evaluation study of an early childhood prevention program. A total of 659 children in intervention and control groups were rated by their parents and teachers on prosocial behavior and relational aggression before and after the program implementation. No mean change in relational aggression was found in either group, whereas an increase in prosocial behavior was found in both groups. Advantages and limitations of the proposed approach are highlighted.
机译:在许多干预和评估研究中,结果变量是使用多方法方法进行评估的,该方法可随时间比较多个组。在本文中,我们展示了如何使用结构方程模型分析从复杂的多特征-多方法-多场合-多组设计中获得的评估数据。特别是,我们展示了如何使用结构方程建模方法来(a)将序数项作为指标处理;(b)测试度量不变性;以及(c)测试潜在变量的均值以检查治疗效果。我们提出了一项针对儿童早期预防计划评估研究的数据的应用程序。干预组和对照组的659名儿童在计划实施前后均由其父母和老师对亲社会行为和关系攻击进行了评分。两组均未发现关系攻击的平均变化,而两组均发现亲社会行为有所增加。强调了所提出方法的优点和局限性。

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