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· 분류 : 외국도서 > 인문/사회 > 사회과학 > 통계
· ISBN : 9781462544646
· 쪽수 : 785쪽
목차
I. Foundations 1. Structural Equation Modeling: An Overview, Rick H. Hoyle 2. A Brief History of Structural Equation Modeling, Ross L. Matsueda 3. The Causal Foundations of Structural Equation Modeling, Judea Pearl 4. Visualizations for Structural Equation Modeling, Jolynn Pek, Erin K. Davisson, & Rick H. Hoyle 5. Latent Variables in Structural Equation Modeling, Kenneth A. Bollen & Rick H. Hoyle 6. Simulation Methods in Structural Equation Modeling, Walter L. Leite, Deborah L. Bandalos, & Zuchao Shen 7. Assumptions in Structural Equation Modeling, Rex B. Kline 8. On the Estimation of Structural Equation Models with Latent Variables, Yunxiao Chen, Irini Moustaki, & Siliang Zhang 9. Structural Equation Modeling as a Framework for Power Analysis, Yi Feng & Gregory R. Hancock 10. Model Fit in Structural Equation Modeling, Stephen G. West, Wei Wu, Daniel McNeish, & Andrea Savord 11. Model Selection in Structural Equation Modeling, Kristopher J. Preacher & Haley E. Yaremych 12. Fitting Structural Equation Models with Missing Data, Craig K. Enders 13. Structural Equation Modeling with the Mplus and lavaan Programs, Christian Geiser II. Basic Models and Applications 14. Confirmatory Factor Analysis, Timothy A. Brown 15. Confirmatory Measurement Models for Dichotomous and Ordered Polytomous Indicators, Natalie A. Koziol 16. Item Parceling in SEM: A Researcher Degree-of-Freedom Ripe for Opportunistic Use, Sonya K. Sterba & Jason D. Rights 17. Using Factor Scores in Structural Equation Modeling, Ines Devlieger & Yves Rosseel 18. Bifactor Measurement Models, Steven P. Reise, Maxwell Mansolf, & Mark G. Haviland 19. Multitrait-Multimethod Models, Michael Eid, Tobias Koch, & Christian Geiser 20. Investigating Measurement Invariance Using Confirmatory Factor Analysis, Keith F. Widaman & Margarita Olivera-Aguilar 21. Flexible Structural Equation Modeling Approaches for Analyzing Means, Marilyn S. Thompson, Yixing Liu, & Samuel B. Green 22. Mediation/Indirect Effects in Structural Equation Modeling, Oscar Gonzalez, Matthew J. Valente, Jeewon Cheong, & David P. MacKinnon 23. Latent Interaction Effects, Augustin Kelava & Holger Brandt 24. Dynamic Moderation with Latent Interactions: General Cross-lagged Panel Models with Interaction Effects Over Time, Michael J. Zyphur & Ozlem Ozkok 25. Psychometric Scale Evaluation Using Structural Equation Modeling and Latent Variable Modeling, Tenko Raykov 26. Multilevel Structural Equation Modeling, Ronald H. Heck & Tingting Reid III. Specialized and Advanced Models and Applications 27. Exploratory Structural Equation Modeling, Alexandre J. S. Morin 28. Structural Equation Modeling with Small Samples and Many Variables, Katerina M. Marcoulides, Ke-Hai Yuan, & Lifang Deng 29. Mixture Models, Douglas Steinley 30. Latent Curve Modeling of Longitudinal Growth Data, Kevin J. Grimm & John J. McArdle 31. Dynamic Structural Equation Modeling as a Combination of Time Series Modeling, Multilevel Modeling, and Structural Equation Modeling, Ellen L. Hamaker, Tihomir Asparouhov, & Bengt Muthn 32. Continuous-Time Dynamic Models: Connections to Structural Equation Models and Other Discrete-Time Models, Sy-Miin Chow, Diane Losardo, Jonathan Park, & Peter C. M. Molenaar 33. Latent Trait-State Models, David A. Cole & Qimin Liu 34. Longitudinal Models for Assessing Dynamics in Dyadic Data, Meng Chen, Hairong Song, & Emilio Ferrer 35. Structural Equation Modeling for Genetic Data, Susanne Bruins, Sanja Franić, Conor V. Dolan, Denny Borsboom, & Dorret I. Boomsma 36. Structural Equation Modeling (SEM)-Based Meta-Analysis, Mike W.-L. Cheung 37. Nonlinear Structural Equation Models: Advanced Methods and Applications, Jeffrey R. Harring & Jinwang Zou 38. Foundations and Extensions of Bayesian Structural Equation Modeling, Sarah Depaoli, David Kaplan, & Sonja D. Winter 39. Machine-Learning Approaches to Structural Equation Modeling, Andreas M. Brandmaier & Ross C. Jacobucci