预设路径模型及其在认知心理学研究中的应用

预设路径模型(Fixed-links modeling)是在结构方程模型框架下发展出的用于分析心理学实验数据的统计模型。该类模型的主要特征是根据前期理论基础和实验设计,通过预先设定模型中显变量与潜变量之间的因素载荷矩阵实现对显变量方差的拆分。因素载荷矩阵的设定主要基于实验水平与所表征的心理过程之间的关系,选取相应函数来表征不同实验水平之间的变化趋势。该模型在表征工作记忆、注意和学习的内部加工过程及揭示不同认知过程的具体联系中发挥了重要作用。

Fixed-links modeling and its application in cognitive psychology research

Fixed-links modeling (FLM) is theory-guided statistical modeling for the purpose of analyzing experimental data in the framework of structural equation modeling (SEM).The main characteristic of a fixed-links model is that the loadings of the manifest variables on the latent ones are pre-fixed according to theory-based expectations.The fixation of loadings enables the decomposition of variances and covariances originating from experimental data into several parts each representing a unique source of variances.The loadings are frequently constrained according to functions that reflect the relationship between treatment levels and underlying cognitive processes.FLM has been widely used in representing processes underlying working memory,attention,and learning.It also plays an important part in investigating the relationships among these abilities and their sources.