Simple, Efficient and Distribution-free Approach to Interaction Effects in Complex Structural Equation Models
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DOI: 10.1007/s11135-006-9050-6
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References listed on IDEAS
- Albert Satorra, 1990. "Robustness issues in structural equation modeling: a review of recent developments," Quality & Quantity: International Journal of Methodology, Springer, vol. 24(4), pages 367-386, November.
- Jost Reinecke, 2002. "Nonlinear Structural Equation Models with the Theory of Planned Behavior: Comparison of Multiple Group and Latent Product Term Analyses," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(2), pages 93-112, May.
- Andreas Klein & Helfried Moosbrugger, 2000. "Maximum likelihood estimation of latent interaction effects with the LMS method," Psychometrika, Springer;The Psychometric Society, vol. 65(4), pages 457-474, December.
- Mònica González & Germà Coenders & Ferran Casas, 2008. "Using Non-linear Models for a Complexity Approach to Psychological Well-being," Quality & Quantity: International Journal of Methodology, Springer, vol. 42(1), pages 1-21, February.
- Gerhard Arminger & Bengt Muthén, 1998. "A Bayesian approach to nonlinear latent variable models using the Gibbs sampler and the metropolis-hastings algorithm," Psychometrika, Springer;The Psychometric Society, vol. 63(3), pages 271-300, September.
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- Monica Palma & Veronica Distefano & Alessandra Spennato, 2019. "Quality Assessment of the Oncology Health Service in a Public Hospital," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 327-343, November.
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Keywords
Interaction effects; structural equation models; indirect effects; non-linear constraints; mean structure; normality assumption;All these keywords.
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