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Structural Equation Modeling: A Multidisciplinary Journal Volume 22, 2015 - Issue 3
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Articles

Transformation Structural Equation Models With Highly Nonnormal and Incomplete Data

Pengfei LiuJiangsu Normal University, Xuzhou, China and Chinese University of Hong Kong
,
Ji ChenChinese University of Hong Kong
,
Zhaohua LuUniversity of North Carolina, Chapel Hill
&
Xinyuan SongChinese University of Hong KongCorrespondence[email protected]
Pages 401-415 | Published online: 12 Dec 2014

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Chuchu Wang, Qi Yang, Xiaoxiao Zhou & Xinyuan Song. (2023) Bayesian Quantile Latent Factor on Image Regression. Structural Equation Modeling: A Multidisciplinary Journal 30:1, pages 70-85.
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Yifan Wang, Xiang-Nan Feng & Xin-Yuan Song. (2016) Bayesian Quantile Structural Equation Models. Structural Equation Modeling: A Multidisciplinary Journal 23:2, pages 246-258.
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Maggie M. Cheng & Rick D. Hackett. (2021) A critical review of algorithms in HRM: Definition, theory, and practice. Human Resource Management Review 31:1, pages 100698.
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Mikko Rönkkö & Miguel I. Aguirre-Urreta. (2020) Cautionary Note on the Two-Step Transformation to Normality. Journal of Information Systems 34:1, pages 151-166.
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Cécile Proust-Lima, Viviane Philipps, Jean-François Dartigues, David A. Bennett, M Maria Glymour, Hélène Jacqmin-Gadda & Cécilia Samieri. (2017) Are latent variable models preferable to composite score approaches when assessing risk factors of change? Evaluation of type-I error and statistical power in longitudinal cognitive studies. Statistical Methods in Medical Research 28:7, pages 1942-1957.
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Niansheng Tang, Ying Wu & Dan Chen. (2018) Semiparametric Bayesian analysis of transformation linear mixed models. Journal of Multivariate Analysis 166, pages 225-240.
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