结构方程建模
潜变量
潜变量模型
计量经济学
面板数据
无效假设
心理学
潜在增长模型
阶乘
面板分析
变量(数学)
计算机科学
认知心理学
数学
人工智能
机器学习
发展心理学
数学分析
作者
Todd D. Little,Kristopher J. Preacher,James P. Selig,Noel A. Card
标识
DOI:10.1177/0165025407077757
摘要
We review fundamental issues in one traditional structural equation modeling (SEM) approach to analyzing longitudinal data — cross-lagged panel designs. We then discuss a number of new developments in SEM that are applicable to analyzing panel designs. These issues include setting appropriate scales for latent variables, specifying an appropriate null model, evaluating factorial invariance in an appropriate manner, and examining both direct and indirect (mediated), effects in ways better suited for panel designs. We supplement each topic with discussion intended to enhance conceptual and statistical understanding.
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