IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v22y1994i3p376-398.html
   My bibliography  Save this article

Multilevel Covariance Structure Analysis

Author

Listed:
  • BENGT O. MUTHÉN

    (University of California, Los Angeles)

Abstract

This article gives an introduction to some new techniques for multilevel covariance structure modeling with latent variables. Although these techniques only incorporate a subset of models that are relevant to multilevel data, the techniques do provide a large set of new analysis possibilities and have the advantage that they only require conventional structural equation modeling software. The presentation draws on methodology presented in earlier works by the author.

Suggested Citation

  • Bengt O. Muthã‰N, 1994. "Multilevel Covariance Structure Analysis," Sociological Methods & Research, , vol. 22(3), pages 376-398, February.
  • Handle: RePEc:sae:somere:v:22:y:1994:i:3:p:376-398
    DOI: 10.1177/0049124194022003006
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124194022003006
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0049124194022003006?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
    ---><---

    References listed on IDEAS

    as
    1. N. Longford & B. Muthén, 1992. "Factor analysis for clustered observations," Psychometrika, Springer;The Psychometric Society, vol. 57(4), pages 581-597, December.
    Full references (including those not matched with items on IDEAS)

    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. Jonathan Schweig, 2014. "Multilevel Factor Analysis by Model Segregation," Journal of Educational and Behavioral Statistics, , vol. 39(5), pages 394-422, October.
    2. Asim Ansari & Kamel Jedidi & Sharan Jagpal, 2000. "A Hierarchical Bayesian Methodology for Treating Heterogeneity in Structural Equation Models," Marketing Science, INFORMS, vol. 19(4), pages 328-347, August.
    3. David B. Dunson & Zhen Chen & Jean Harry, 2003. "A Bayesian Approach for Joint Modeling of Cluster Size and Subunit-Specific Outcomes," Biometrics, The International Biometric Society, vol. 59(3), pages 521-530, September.
    4. Asim Ansari & Kamel Jedidi & Laurette Dube, 2002. "Heterogeneous factor analysis models: A bayesian approach," Psychometrika, Springer;The Psychometric Society, vol. 67(1), pages 49-77, March.
    5. Junhao Pan & Edward Haksing Ip & Laurette Dubé, 2020. "Multilevel Heterogeneous Factor Analysis and Application to Ecological Momentary Assessment," Psychometrika, Springer;The Psychometric Society, vol. 85(1), pages 75-100, March.
    6. 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.
    7. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "Generalized multilevel structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 167-190, June.
    8. Steven Boker & Michael Neale & Hermine Maes & Michael Wilde & Michael Spiegel & Timothy Brick & Jeffrey Spies & Ryne Estabrook & Sarah Kenny & Timothy Bates & Paras Mehta & John Fox, 2011. "OpenMx: An Open Source Extended Structural Equation Modeling Framework," Psychometrika, Springer;The Psychometric Society, vol. 76(2), pages 306-317, April.
    9. Cécile Proust & Hélène Jacqmin-Gadda & Jeremy M. G. Taylor & Julien Ganiayre & Daniel Commenges, 2006. "A Nonlinear Model with Latent Process for Cognitive Evolution Using Multivariate Longitudinal Data," Biometrics, The International Biometric Society, vol. 62(4), pages 1014-1024, December.
    10. Sik-Yum Lee & Jian-Qing Shi, 2001. "Maximum Likelihood Estimation of Two-Level Latent Variable Models with Mixed Continuous and Polytomous Data," Biometrics, The International Biometric Society, vol. 57(3), pages 787-794, September.
    11. Sik-Yum Lee & Sin-Yu Tsang, 1999. "Constrained maximum likelihood estimation of two-level covariance structure model via EM type algorithms," Psychometrika, Springer;The Psychometric Society, vol. 64(4), pages 435-450, December.
    12. Ke-Hai Yuan & Peter Bentler, 2004. "On the asymptotic distributions of two statistics for two-level covariance structure models within the class of elliptical distributions," Psychometrika, Springer;The Psychometric Society, vol. 69(3), pages 437-457, September.
    13. Ke-Hai Yuan & Peter Bentler, 2002. "On normal theory based inference for multilevel models with distributional violations," Psychometrika, Springer;The Psychometric Society, vol. 67(4), pages 539-561, December.
    14. Bengt Muthén & Tihomir Asparouhov, 2018. "Recent Methods for the Study of Measurement Invariance With Many Groups," Sociological Methods & Research, , vol. 47(4), pages 637-664, November.

    More about this item

    Statistics

    Access and download statistics

    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:sae:somere:v:22:y:1994:i:3:p:376-398. 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: SAGE Publications (email available below). General contact details of provider: .

    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.