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Model comparison of nonlinear structural equation models with fixed covariates

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  • Sik-Yum Lee
  • Xin-Yuan Song

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  • Sik-Yum Lee & Xin-Yuan Song, 2003. "Model comparison of nonlinear structural equation models with fixed covariates," Psychometrika, Springer;The Psychometric Society, vol. 68(1), pages 27-47, March.
    • Handle: RePEc:spr:psycho:v:68:y:2003:i:1:p:27-47
    DOI: 10.1007/BF02296651
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    References listed on IDEAS

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    1. J.‐Q. Shi & S.‐Y. Lee, 2000. "Latent variable models with mixed continuous and polytomous data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(1), pages 77-87.
    2. Yosihiko Ogata, 1990. "A Monte Carlo method for an objective Bayesian procedure," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 42(3), pages 403-433, September.
    3. Sylvia. Richardson & Peter J. Green, 1997. "On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion)," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(4), pages 731-792.
    4. Sik-Yum Lee & Hong-Tu Zhu, 2002. "Maximum likelihood estimation of nonlinear structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 67(2), pages 189-210, June.
    5. P. Bentler, 1983. "Some contributions to efficient statistics in structural models: Specification and estimation of moment structures," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 493-517, December.
    6. Bagozzi, Richard P & Baumgartner, Hans & Yi, Youjae, 1992. "State versus Action Orientation and the Theory of Reasoned Action: An Application to Coupon Usage," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 18(4), pages 505-518, March.
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    Citations

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    Cited by:

    1. Pietro Lovaglio & Roberto Boselli, 2015. "Simulation studies of structural equation models with covariates in a redundancy analysis framework," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 881-890, May.
    2. Zhang, Yan-Qing & Tian, Guo-Liang & Tang, Nian-Sheng, 2016. "Latent variable selection in structural equation models," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 190-205.
    3. Vinícius Diniz Mayrink & Renato Valladares Panaro & Marcelo Azevedo Costa, 2021. "Structural equation modeling with time dependence: an application comparing Brazilian energy distributors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(2), pages 353-383, June.
    4. Karin Schermelleh-Engel & Christina Werner & Andreas Klein & Helfried Moosbrugger, 2010. "Nonlinear structural equation modeling: is partial least squares an alternative?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 94(2), pages 167-184, June.
    5. Sik-Yum Lee & Xin-Yuan Song, 2007. "A Unified Maximum Likelihood Approach for Analyzing Structural Equation Models With Missing Nonstandard Data," Sociological Methods & Research, , vol. 35(3), pages 352-381, February.
    6. Lee, Sik-Yum & Song, Xin-Yuan, 2008. "On Bayesian estimation and model comparison of an integrated structural equation model," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4814-4827, June.
    7. Sik-Yum Lee & Ye-Mao Xia, 2008. "A Robust Bayesian Approach for Structural Equation Models with Missing Data," Psychometrika, Springer;The Psychometric Society, vol. 73(3), pages 343-364, September.

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