6. TESTING MULTIPLE NONLINEAR EFFECTS IN STRUCTURAL EQUATION MODELING: A COMPARISON OF ALTERNATIVE ESTIMATION APPROACHES
暂无分享,去创建一个
[1] Fan Yang,et al. Nonlinear structural equation models: The Kenny-Judd model with Interaction effects , 1996 .
[2] Helfried Moosbrugger,et al. Challenges in Nonlinear Structural Equation Modeling , 2007 .
[3] Bengt O. Muthén,et al. Quasi-Maximum Likelihood Estimation of Structural Equation Models With Multiple Interaction and Quadratic Effects , 2007 .
[4] Robert C. MacCallum,et al. DISTINGUISHING BETWEEN MODERATOR AND QUADRATIC EFFECTS IN MULTIPLE REGRESSION , 1995 .
[5] George A. Marcoulides,et al. Interaction and Nonlinear Effects in Structural Equation Modeling , 1998 .
[6] M. Prinstein,et al. Adolescent girls' and boys' weight-related health behaviors and cognitions: associations with reputation- and preference-based peer status. , 2006, Health psychology : official journal of the Division of Health Psychology, American Psychological Association.
[7] J. Bois,et al. Relation between teachers' early expectations and students' later perceived competence in physical education classes: Autonomy-supportive climate as a moderator. , 2006 .
[8] L. Humphreys,et al. Assessing spurious "moderator effects": Illustrated substantively with the hypothesized ("synergistic") relation between spatial and mathematical ability. , 1990, Psychological bulletin.
[9] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[10] L. E. Jones,et al. Analysis of multiplicative combination rules when the causal variables are measured with error. , 1983 .
[11] James Algina,et al. Comparison of Methods for Estimating and Testing Latent Variable Interactions , 2002 .
[12] Fan Yang Jonsson. Non-linear structural equation models : simulation studies of the Kenny-Judd model , 1997 .
[13] H. Marsh,et al. Structural equation models of latent interactions: evaluation of alternative estimation strategies and indicator construction. , 2004, Psychological methods.
[14] Donald W. Marquardt,et al. Comment: You Should Standardize the Predictor Variables in Your Regression Models , 1980 .
[15] Karl G. Jöreskog,et al. Lisrel 8: User's Reference Guide , 1997 .
[16] I. Ajzen. The theory of planned behavior , 1991 .
[17] Helfried Moosbrugger,et al. Maximum likelihood estimation of latent interaction effects with the LMS method , 2000 .
[18] Jacob Cohen,et al. Applied multiple regression/correlation analysis for the behavioral sciences , 1979 .
[19] Yoav Ganzach,et al. Misleading Interaction and Curvilinear Terms , 1997 .
[20] James Jaccard,et al. Measurement error in the analysis of interaction effects between continuous predictors using multiple regression: Multiple indicator and structural equation approaches. , 1995 .
[21] Larry E. Toothaker,et al. Multiple Regression: Testing and Interpreting Interactions , 1991 .
[22] Yasuo Amemiya,et al. Estimation for Polynomial Structural Equation Models , 2000 .
[23] D. A. Kenny,et al. Estimating the nonlinear and interactive effects of latent variables. , 1984 .
[24] M. Elliott,et al. Drivers' compliance with speed limits: an application of the theory of planned behavior. , 2003, The Journal of applied psychology.
[25] Helfried Moosbrugger,et al. Multicollinearity and missing constraints: A comparison of three approaches for the analysis of latent nonlinear effects. , 2008 .