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Structural Equation Models: A Review With Applications to Environmental Epidemiology

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  • Sanchez, Brisa N.
  • Budtz-Jorgensen, Esben
  • Ryan, Louise M.
  • Hu, Howard

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  • Sanchez, Brisa N. & Budtz-Jorgensen, Esben & Ryan, Louise M. & Hu, Howard, 2005. "Structural Equation Models: A Review With Applications to Environmental Epidemiology," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1443-1455, December.
    • Handle: RePEc:bes:jnlasa:v:100:y:2005:p:1443-1455
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    1. 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.
    2. Bonnie E. Shook-Sa & Ding-Geng Chen & Haibo Zhou, 2017. "Using Structural Equation Modeling to Assess the Links between Tobacco Smoke Exposure, Volatile Organic Compounds, and Respiratory Function for Adolescents Aged 6 to 18 in the United States," IJERPH, MDPI, vol. 14(10), pages 1-12, September.
    3. Meenakshi Rao & Linda A. George & Vivek Shandas & Todd N. Rosenstiel, 2017. "Assessing the Potential of Land Use Modification to Mitigate Ambient NO 2 and Its Consequences for Respiratory Health," IJERPH, MDPI, vol. 14(7), pages 1-19, July.
    4. D. B. Woodard & T. M. T. Love & S. W. Thurston & D. Ruppert & S. Sathyanarayana & S. H. Swan, 2013. "Latent factor regression models for grouped outcomes," Biometrics, The International Biometric Society, vol. 69(3), pages 785-794, September.
    5. Xin-Yuan Song & Zhao-Hua Lu & Jing-Heng Cai & Edward Ip, 2013. "A Bayesian Modeling Approach for Generalized Semiparametric Structural Equation Models," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 624-647, October.
    6. Klaus Holst & Esben Budtz-Jørgensen, 2013. "Linear latent variable models: the lava-package," Computational Statistics, Springer, vol. 28(4), pages 1385-1452, August.
    7. Amy LaLonde & Tanzy Love & Sally W. Thurston & Philip W. Davidson, 2020. "Discovering structure in multiple outcomes models for tests of childhood neurodevelopment," Biometrics, The International Biometric Society, vol. 76(3), pages 874-885, September.
    8. Song, Xin-Yuan & Tang, Nian-Sheng & Chow, Sy-Miin, 2012. "A Bayesian approach for generalized random coefficient structural equation models for longitudinal data with adjacent time effects," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4190-4203.
    9. Popli, Gurleen & Gladwell, Daniel & Tsuchiya, Aki, 2013. "Estimating the critical and sensitive periods of investment in early childhood: A methodological note," Social Science & Medicine, Elsevier, vol. 97(C), pages 316-324.
    10. Luca Zanin, 2013. "Detecting Unobserved Heterogeneity in the Relationship Between Subjective Well-Being and Satisfaction in Various Domains of Life Using the REBUS-PLS Path Modelling Approach: A Case Study," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(1), pages 281-304, January.
    11. Sally W. Thurston & David Ruppert & Philip W. Davidson, 2009. "Bayesian Models for Multiple Outcomes Nested in Domains," Biometrics, The International Biometric Society, vol. 65(4), pages 1078-1086, December.
    12. Alexis E. Zavez & Emeir M. McSorley & Alison J. Yeates & Sally W. Thurston, 2023. "A Bayesian Partial Membership Model for Multiple Exposures with Uncertain Group Memberships," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(3), pages 377-400, September.
    13. E. Andrés Houseman & Carmen Marsit & Margaret Karagas & Louise M. Ryan, 2007. "Penalized Item Response Theory Models: Application to Epigenetic Alterations in Bladder Cancer," Biometrics, The International Biometric Society, vol. 63(4), pages 1269-1277, December.
    14. Kamble, Sachin S. & Gunasekaran, Angappa & Kumar, Vikas & Belhadi, Amine & Foropon, Cyril, 2021. "A machine learning based approach for predicting blockchain adoption in supply Chain," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    15. Tyler J. VanderWeele & Stijn Vansteelandt, 2022. "A statistical test to reject the structural interpretation of a latent factor model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 2032-2054, November.

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