IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v69y2004i3p421-436.html
   My bibliography  Save this article

Structural equation modeling with heavy tailed distributions

Author

Listed:
  • Ke-Hai Yuan
  • Peter Bentler
  • Wai Chan

Abstract

No abstract is available for this item.

Suggested Citation

  • Ke-Hai Yuan & Peter Bentler & Wai Chan, 2004. "Structural equation modeling with heavy tailed distributions," Psychometrika, Springer;The Psychometric Society, vol. 69(3), pages 421-436, September.
  • Handle: RePEc:spr:psycho:v:69:y:2004:i:3:p:421-436
    DOI: 10.1007/BF02295644
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02295644
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/BF02295644?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gerhard Arminger & Petra Stein & Jörg Wittenberg, 1999. "Mixtures of conditional mean- and covariance-structure models," Psychometrika, Springer;The Psychometric Society, vol. 64(4), pages 475-494, December.
    2. N. A. Campbell, 1982. "Robust Procedures in Multivariate Analysis II. Robust Canonical Variate Analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(1), pages 1-8, March.
    3. Hu, Feifang & Hu, Jianhua, 2000. "A note on breakdown theory for bootstrap methods," Statistics & Probability Letters, Elsevier, vol. 50(1), pages 49-53, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kajalo, Sami & Lindblom, Arto, 2010. "How retail entrepreneurs perceive the link between surveillance, feeling of security, and competitiveness of the retail store? A structural model approach," Journal of Retailing and Consumer Services, Elsevier, vol. 17(4), pages 300-305.
    2. Alexander Robitzsch, 2022. "Comparing the Robustness of the Structural after Measurement (SAM) Approach to Structural Equation Modeling (SEM) against Local Model Misspecifications with Alternative Estimation Approaches," Stats, MDPI, vol. 5(3), pages 1-42, July.
    3. Mishra, Debi P., 2013. "Firms’ strategic response to service uncertainty: An empirical signaling study," Australasian marketing journal, Elsevier, vol. 21(3), pages 187-197.
    4. Ke-Hai Yuan & Wai Chan & Yubin Tian, 2016. "Expectation-robust algorithm and estimating equations for means and dispersion matrix with missing data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 68(2), pages 329-351, April.
    5. Masood Badri & Ali Alnuaimi & Guang Yang & Asma Al Rashidi & Rabaa Al Sumaiti, 2017. "A Structural Equation Model of Determinants of the Perceived Impact of Teachers’ Professional Development—The Abu Dhabi Application," SAGE Open, , vol. 7(2), pages 21582440177, April.
    6. Stas Kolenikov, 2011. "Structural equation modeling using gllamm, confa, and gmm," German Stata Users' Group Meetings 2011 01, Stata Users Group.
    7. Ke-Hai Yuan & Zhiyong Zhang, 2012. "Robust Structural Equation Modeling with Missing Data and Auxiliary Variables," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 803-826, October.
    8. Lifang Deng & Ke-Hai Yuan, 2016. "Comparing Latent Means Without Mean Structure Models: A Projection-Based Approach," Psychometrika, Springer;The Psychometric Society, vol. 81(3), pages 802-829, September.
    9. Zhiyong Zhang, 2013. "Bayesian growth curve models with the generalized error distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1779-1795, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alfò, Marco & Carbonari, Lorenzo & Trovato, Giovanni, 2023. "On the effects of taxation on growth: an empirical assessment," Macroeconomic Dynamics, Cambridge University Press, vol. 27(5), pages 1289-1318, July.
    2. Wu, Qiang & Yao, Weixin, 2016. "Mixtures of quantile regressions," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 162-176.
    3. Bacci, Silvia & Bartolucci, Francesco & Pieroni, Luca, 2012. "A causal analysis of mother’s education on birth inequalities," MPRA Paper 38754, University Library of Munich, Germany.
    4. Kosinski, Andrzej S., 1998. "A procedure for the detection of multivariate outliers," Computational Statistics & Data Analysis, Elsevier, vol. 29(2), pages 145-161, December.
    5. Kamiya, Hidehiko & Eguchi, Shinto, 2001. "A Class of Robust Principal Component Vectors," Journal of Multivariate Analysis, Elsevier, vol. 77(2), pages 239-269, May.
    6. Williams, John & Temme, Dirk & Hildebrandt, Lutz, 2002. "A Monte Carlo study of structural equation models for finite mixtures," SFB 373 Discussion Papers 2002,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    7. Fokoué, Ernest, 2005. "Mixtures of factor analyzers: an extension with covariates," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 370-384, August.
    8. Giuliano Galimberti & Lorenzo Nuzzi & Gabriele Soffritti, 2021. "Covariance matrix estimation of the maximum likelihood estimator in multivariate clusterwise linear regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 235-268, March.
    9. Anders Skrondal & Sophia Rabe‐Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745, December.
    10. Terry Elrod & Gerald Häubl & Steven Tipps, 2012. "Parsimonious Structural Equation Models for Repeated Measures Data, with Application to the Study of Consumer Preferences," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 358-387, April.
    11. DongHyuk Lee & Raymond J. Carroll & Samiran Sinha, 2017. "Frequentist standard errors of Bayes estimators," Computational Statistics, Springer, vol. 32(3), pages 867-888, September.
    12. Temme, Dirk & Williams, John R. & Hildebrandt, Lutz, 2002. "Structural equation models for finite mixtures: Simulation results and empirical applications," SFB 373 Discussion Papers 2002,33, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    13. Cai, Jing-Heng & Song, Xin-Yuan & Lam, Kwok-Hap & Ip, Edward Hak-Sing, 2011. "A mixture of generalized latent variable models for mixed mode and heterogeneous data," Computational Statistics & Data Analysis, Elsevier, vol. 55(11), pages 2889-2907, November.
    14. Wu, Qiang & Sampson, Allan R., 2009. "Mixture modeling with applications in schizophrenia research," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2563-2572, May.
    15. Roberts, Yvonne Humenay & English, Diana & Thompson, Richard & White, Catherine Roller, 2018. "The impact of childhood stressful life events on health and behavior in at-risk youth," Children and Youth Services Review, Elsevier, vol. 85(C), pages 117-126.
    16. Walter Krämer, 2022. "Interview mit Gerhard Arminger," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 16(3), pages 287-294, December.
    17. Peter Verboon & Ivo Lans, 1994. "Robust canonical discriminant analysis," Psychometrika, Springer;The Psychometric Society, vol. 59(4), pages 485-507, December.
    18. Pires, Ana M. & Branco, João A., 2010. "Projection-pursuit approach to robust linear discriminant analysis," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2464-2485, November.
    19. Cecilie Thogersen-Ntoumani & Julie Black & Magnus Lindwall & Anna Whittaker & George M. Balanos, 2017. "Presenteeism, stress resilience, and physical activity in older manual workers: a person-centred analysis," European Journal of Ageing, Springer, vol. 14(4), pages 385-396, December.
    20. Erik Meijer & Susann Rohwedder & Tom Wansbeek, 2008. "Prediction of Latent Variables in a Mixture of Structural Equation Models, with an Application to the Discrepancy Between Survey and Register Data," Working Papers 584, RAND Corporation.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:psycho:v:69:y:2004:i:3:p:421-436. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.