A Growth of Hierarchical Autoregression Model for Capturing Individual Differences in Changes of Dynamic Characteristics of Psychological Processes

IF 2.5 2区心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Structural Equation Modeling: A Multidisciplinary Journal Pub Date : 2024-10-03 DOI:10.1080/10705511.2024.2402328

Yanling Li, Lindy Williams, Chelsea Muth, Saeideh Heshmati, Sy-Miin Chow, Zita Oravecz

引用次数: 0

Abstract

Several methodological innovations have been advanced in the past decades that combine growth curve models (GCMs) with models of autoregressive (AR) processes. However, most of these approaches do ...

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捕捉心理过程动态特征变化中的个体差异的分层自回归模型的发展

在过去的几十年中，有几项方法创新将增长曲线模型（GCM）与自回归（AR）过程模型相结合。然而，这些方法大多 ...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Structural Equation Modeling: A Multidisciplinary Journal 数学-数学跨学科应用

CiteScore

8.70

自引率

11.70%

发文量

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.