教师园地:用于潜在增长曲线调解敏感性分析的 R Shiny 应用程序。

IF 2.5 2区 心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Eric S Kruger, Davood Tofighi, Yu-Yu Hsiao, David P MacKinnon, M Lee Van Horn, Katie Witkiewitz
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引用次数: 0

摘要

行为改变的机制是假设干预措施导致结果改变的过程。推荐使用潜伏增长曲线中介模型(LGCMM)来研究行为变化的机制,因为 LGCMM 模型确定了从中介变量到结果变量之间变化的时间优先性。相关增强中介敏感性分析(CAMSA)应用程序对 LGCMM 模型进行敏感性分析,以评估中介路径(机制)是否对潜在的混杂变量具有稳健性。本文介绍了 CAMSA 方法,并将其应用于模拟数据和一项探索药物使用障碍治疗中的变化机制的研究数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Teacher's Corner: An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation.

Teacher's Corner: An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation.

Mechanisms of behavior change are the processes through which interventions are hypothesized to cause changes in outcomes. Latent growth curve mediation models (LGCMM) are recommended for investigating the mechanisms of behavior change because LGCMM models establish temporal precedence of change from the mediator to the outcome variable. The Correlated Augmented Mediation Sensitivity Analyses (CAMSA) App implements sensitivity analysis for LGCMM models to evaluate if a mediating path (mechanism) is robust to potential confounding variables. The CAMSA approach is described and applied to simulated data, and data from a research study exploring a mechanism of change in the treatment of substance use disorder.

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来源期刊
CiteScore
8.70
自引率
11.70%
发文量
71
审稿时长
>12 weeks
期刊介绍: Structural Equation Modeling: A Multidisciplinary Journal publishes refereed scholarly work from all academic disciplines interested in structural equation modeling. These disciplines include, but are not limited to, psychology, medicine, sociology, education, political science, economics, management, and business/marketing. Theoretical articles address new developments; applied articles deal with innovative structural equation modeling applications; the Teacher’s Corner provides instructional modules on aspects of structural equation modeling; book and software reviews examine new modeling information and techniques; and advertising alerts readers to new products. Comments on technical or substantive issues addressed in articles or reviews published in the journal are encouraged; comments are reviewed, and authors of the original works are invited to respond.
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