摘要
简要回顾了分析显变量交互效应的常用方法。详细讨论了目前分析潜变量交互效应的主要方法，包括用潜变量的因子得分做回归分析、分组线性结构方程模型分析、加入乘积项的结构方程模型分析和两步最小二乘回归分析，并比较和评价了这些方法的优缺点。最后归纳了潜变量交互效应分析方法的研究趋势，并介绍了新近进展（包括LMS方法和GAPI方法）。
Analysis of interaction, the phenomenon that the effect (including the size and direction) of a certain independent variable (or predictor) depends on the state (size, value) of another independent variable, has always been important in psychological or social research. Methods for the analysis of interaction effects between observed variables were briefly reviewed. The main concern of the article was the detailed comparison and discussion on the analysis of latent variable interactions. Four basic approaches, including regression on factor scores, multiple-group structural equation modeling, structural equation modeling with product terms, and two-stage least square regression, were illustrated and contrasted. Advances in these and other analytical methods, including recently developed latent moderated structural equations (LMS) approach and generalized appended product indicator (GAPI) procedure, were also described and evaluated.
出处
《心理科学进展》
CSSCI
CSCD
北大核心
2003年第5期593-599,共7页
Advances in Psychological Science
基金
教育部"十五"重点课题(DBA010169)
中国国家留学基金委员会资助
香港中文大学资助
华南师范大学心理应用研究中心(教育部
