IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb373/200233.html
   My bibliography  Save this paper

Structural equation models for finite mixtures: Simulation results and empirical applications

Author

Listed:
  • Temme, Dirk
  • Williams, John R.
  • Hildebrandt, Lutz

Abstract

Unobserved heterogeneity is a serious but often neglected problem in structural equation modelling (SEM) challenging the validity of many empirical results. Recently, a finite mixture approach to SEM has been proposed to resolve this problem but until now only a few studies analyse the performance of the relevant software. The contribution of this paper is twofold: First, results from a Monte Carlo study into the properties of the program system MECOSA are presented. Second, an empirical application to data from a large-scale consumer survey in the fast moving consumer goods industry is described.

Suggested Citation

  • 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.
  • Handle: RePEc:zbw:sfb373:200233
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/65294/1/726383082.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Conor Dolan & Han Maas, 1998. "Fitting multivariage normal finite mixtures subject to structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 63(3), pages 227-253, September.
    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. Yiu-Fai Yung, 1997. "Finite mixtures in confirmatory factor-analysis models," Psychometrika, Springer;The Psychometric Society, vol. 62(3), pages 297-330, September.
    4. Kamel Jedidi & Harsharanjeet S. Jagpal & Wayne S. DeSarbo, 1997. "Finite-Mixture Structural Equation Models for Response-Based Segmentation and Unobserved Heterogeneity," Marketing Science, INFORMS, vol. 16(1), pages 39-59.
    5. Venkatram Ramaswamy & Wayne S. Desarbo & David J. Reibstein & William T. Robinson, 1993. "An Empirical Pooling Approach for Estimating Marketing Mix Elasticities with PIMS Data," Marketing Science, INFORMS, vol. 12(1), pages 103-124.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    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:zbw:sfb373:200233. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics). General contact details of provider: http://edirc.repec.org/data/sfhubde.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.