潜变量交互效应建模方法演变与简化被引量：87

Evolution and Simplification of the Approaches to Estimating Structural Equation Models with Latent Interaction

下载PDF

导出

摘要综述了近年来加入乘积指标的潜变量交互效应建模方法,从产生乘积指标的策略、参数约束方法、均值结构与指标中心化的关系三个方面,讨论了建模方法的简化进程。最后总结出同类方法中比较简洁又不失精确的潜变量交互效应建模方法——无需均值结构的无约束方法,并给出了建模步骤。 Recent researches on structural equation modeling with latent interaction were reviewed.The processes of simplification of the modeling were discussed from the three aspects：the strategies of creating product indicators,the approaches of constraining parameters,and the requirement of the mean structure and its relation to indicator-centering.The unconstrained model without using the mean structure was recommended,and the steps for the modeling were summarized.

作者温忠麟吴艳

机构地区华南师范大学心理应用研究中心香港考试及评核局

出处《心理科学进展》 CSSCI CSCD 北大核心 2010年第8期1306-1313,共8页 Advances in Psychological Science

基金国家自然科学基金项目(30870784)资助

关键词潜变量交互效应结构方程指标均值结构 latent variable interaction effect structural equation model indicator mean structure

分类号 B841.2 [哲学宗教—基础心理学]

引文网络
相关文献

参考文献33

1温忠麟,侯杰泰,马什赫伯特.潜变量交互效应分析方法[J].心理科学进展,2003,11(5):593-599. 被引量：83
2温忠麟,侯杰泰,Herbert W．Marsh.结构方程模型中调节效应的标准化估计[J].心理学报,2008,40(6):729-736. 被引量：118
3吴艳,温忠麟,林冠群.潜变量交互效应建模:告别均值结构[J].心理学报,2009,41(12):1252-1259. 被引量：39
4Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: SAGE Publications.
5Algina, J., & Moulder, B. C. (2001). A note on estimating the Joreskog-Yang model for latent variable interaction using LISREL 8.3. Structural Equation Modeling, 8, 40-52.
6Batista-Foguet, J. M., Coenders, G., & Saris, W. E. (2004). A parsimonious approach to interaction effects in structural equation models: an application to consumer behavior. Working Papers d'ESADE, 183, 1-28.
7Coenders, G., Batista-Foguet, J. M., & Saris, W. E. (2008). Simple, efficient and distribution-free approach to interaction effects in complex structural equation models. Quality & Quantity, 42(3), 369-396.
8Cohen, J., Cohen, R, West, S. G., & Aiken, L. A. (2003). Applied multiple regression~correlation analysis for the behavior sciences (3 ed.). Mahwah, NJ: Erlbaum.
9Fraser, C. (1980). COSAN User's Guide. Toronto, Ontario: The Ontario Institute for Studies in Education.
10Hayduk, L. A. (1987). Structural equation modeling with LISREL: Essential and advances. Baltimore: Johns Hopkins University.

二级参考文献60

1温忠麟,张雷,侯杰泰,刘红云.中介效应检验程序及其应用[J].心理学报,2004,36(5):614-620. 被引量：7273
2温忠麟,侯杰泰,张雷.调节效应与中介效应的比较和应用[J].心理学报,2005,37(2):268-274. 被引量：3048
3温忠麟,张雷,侯杰泰.有中介的调节变量和有调节的中介变量[J].心理学报,2006,38(3):448-452. 被引量：716
4Jaccard, J., & Wan, C. K. (1995). Measurement analysis of interaction effects between error in the continuous predictors using multiple regression: Multiple indicator and structural equation approaches. Psychological Bulletin, 117(2), 348-357.
5Joreskog, K. G., & Yang, F. (1996). Nonlinear structural equation models: The Kenny -Judd model with interaction effects. In G. A. Marcoulides & R. E. Schumacker (Eds.), Advances in structural equation modeling techniques (pp. 57-88). Hillsdale, NJ: LEA.
6Kenny, D., & Judd, C. M. (1984). Estimating the nonlinear and interactive effects of latent variables. Psychological Bulletin, 96, 201-210.
7Lin, G. C,, Wen, Z., Marsh, H. W., & Lin, H. S. (in press). Structural equation models of latent interactions: clarification of orthogonalizing and double-mean-centering strategies. Structural Equation Modeling.
8Little, T.D., Bovaird, J.A., & Widaman,K. F. (2006). On the merits of orthogonalizing powered and product term: Implications for modeling interactions among latent variables. Structural Equation Modeling, 13(4), 497-519.
9Marsh, H. W., Wen, Z., & Hau, K. T. (2004). Structural equation models of latent interactions: Evaluation of alternative estimation strategies and indicator construction. Psychological Methods, 9(3), 275-300.
10Marsh, H. W., Wen, Z., & Hau, K. T. (2006). Structural equation models of latent interaction and quadratic effects. In G. Hancock & R. Mueller (Eds.), A second course in structural equation modeling (pp. 225-265). Greenwich, CT: Information Age.