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Interindividual Differences in Treatment Effects Based on Structural Equation Models with Latent Variables: An EffectLiteR Tutorial

机译:基于结构方程模型与潜在变量的治疗效果的细分差异:effectLiter教程

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The investigation of interindividual differences in the effects of a treatment is challenging, because many constructs-of-interest in psychological research such as depression or anxiety are latent variables and modeling heterogeneity in treatment effects requires interactions and potentially non-linear relationships. In this paper, we present a tutorial of the EffectLiteR approach that allows for estimating individual treatment effects based on latent variable models. We describe step by step how to apply the approach using the EffectLiteR software package with data from the multicenter randomized controlled trial of the Social Phobia Psychotherapy Network (SOPHO-NET) and provide guidelines and recommendations for researchers. The focus of the paper is on explaining the results of a comprehensive effect analysis in an accessible language and on highlighting the opportunities the EffectLiteR approach offers for analyzing interindividual differences in treatment effects.
机译:对治疗效果效应的关联差异的调查是具有挑战性的,因为许多对抑郁或焦虑的心理学研究构建兴趣是潜在的变量,并且在治疗效果中建模异质性需要相互作用和潜在的非线性关系。在本文中,我们提出了效果方法的教程,其允许基于潜在可变模型估计各个治疗效果。我们描述了如何使用EffectLiter软件包使用来自社会恐惧症心理疗法网络(Sopho-Net)的多中心随机对照试验的数据来应用该方法,并为研究人员提供指导方针和建议。本文的重点是通过可访问语言解释综合效果分析的结果,并突出了效果效应方法的机会,用于分析治疗效果的互联差异。

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