IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v9y1990i1p91-97.html
   My bibliography  Save this article

Full maximum likelihood analysis of structural equation models with polytomous variables

Author

Listed:
  • Lee, Sik-Yum
  • Poon, Wai-Yin
  • Bentler, P. M.

Abstract

This paper is concerned with the analysis of structural equation models with polytomous variables. Identification conditions for the basic model are discussed. Theory for the full simultaneous maximum likelihood estimation of the thresholds and the covariance structure parameters is developed. An example is presented to illustrate the method.

Suggested Citation

  • Lee, Sik-Yum & Poon, Wai-Yin & Bentler, P. M., 1990. "Full maximum likelihood analysis of structural equation models with polytomous variables," Statistics & Probability Letters, Elsevier, vol. 9(1), pages 91-97, January.
    • Handle: RePEc:eee:stapro:v:9:y:1990:i:1:p:91-97
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0167-7152(90)90100-L
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

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

    Citations

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


    Cited by:

    1. Florian Schuberth & Jörg Henseler & Theo K. Dijkstra, 2018. "Partial least squares path modeling using ordinal categorical indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 9-35, January.
    2. Katsikatsou, Myrsini & Moustaki, Irini & Md Jamil, Haziq, 2022. "Pairwise likelihood estimation for confirmatory factor analysis models with categorical variables and data that are missing at random," LSE Research Online Documents on Economics 108933, London School of Economics and Political Science, LSE Library.
    3. Luigi Lombardi & Massimiliano Pastore, 2016. "Robust evaluation of fit indices to fake-good perturbation of ordinal data," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(6), pages 2651-2675, November.
    4. Ranalli, Monia & Rocci, Roberto, 2017. "Mixture models for mixed-type data through a composite likelihood approach," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 87-102.
    5. Katsikatsou, Myrsini & Moustaki, Irini & Yang-Wallentin, Fan & Jöreskog, Karl G., 2012. "Pairwise likelihood estimation for factor analysis models with ordinal data," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4243-4258.
    6. Bengt Muthén & Albert Satorra, 1995. "Technical aspects of Muthén's liscomp approach to estimation of latent variable relations with a comprehensive measurement model," Psychometrika, Springer;The Psychometric Society, vol. 60(4), pages 489-503, December.
    7. Monia Ranalli & Roberto Rocci, 2024. "Composite likelihood methods for parsimonious model-based clustering of mixed-type data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(2), pages 381-407, June.
    8. Nuo Xi & Michael W. Browne, 2014. "Contributions to the Underlying Bivariate Normal Method for Factor Analyzing Ordinal Data," Journal of Educational and Behavioral Statistics, , vol. 39(6), pages 583-611, December.
    9. Monia Ranalli & Roberto Rocci, 2017. "A Model-Based Approach to Simultaneous Clustering and Dimensional Reduction of Ordinal Data," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1007-1034, December.
    10. Avinash D. Pathardikar & Sangeeta Sahu, 2014. "Can Visionary Leaders be Role Models for Collaborative Style of Conflict Handling among Teams in IT Organizations?," Management and Labour Studies, XLRI Jamshedpur, School of Business Management & Human Resources, vol. 39(1), pages 103-120, February.
    11. Sik-Yum Lee & Wai-Yin Poon & P. Bentler, 1992. "Structural equation models with continuous and polytomous variables," Psychometrika, Springer;The Psychometric Society, vol. 57(1), pages 89-105, March.
    12. Haoran Zhang & Yunxiao Chen & Xiaoou Li, 2020. "A Note on Exploratory Item Factor Analysis by Singular Value Decomposition," Psychometrika, Springer;The Psychometric Society, vol. 85(2), pages 358-372, June.
    13. Papageorgiou, Ioulia & Moustaki, Irini, 2019. "Sampling of pairs in pairwise likelihood estimation for latent variable models with categorical observed variables," LSE Research Online Documents on Economics 87592, London School of Economics and Political Science, LSE Library.
    14. Adolfo Esparcia & Joan Guárdia Olmos, 2001. "The Relationship of the Degree of Exposure to a Technological Disaster and Emotional Response: A Structural Model Approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 35(2), pages 161-171, May.
    15. Myrsini Katsikatsou & Irini Moustaki, 2016. "Pairwise Likelihood Ratio Tests and Model Selection Criteria for Structural Equation Models with Ordinal Variables," Psychometrika, Springer;The Psychometric Society, vol. 81(4), pages 1046-1068, December.
    16. Katia Iglesias & Christian Suter & Tugce Beycan & B. P. Vani, 2017. "Exploring Multidimensional Well-Being in Switzerland: Comparing Three Synthesizing Approaches," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 134(3), pages 847-875, December.
    17. Zhang, Haoran & Chen, Yunxiao & Li, Xiaoou, 2020. "A note on exploratory item factor analysis by singular value decomposition," LSE Research Online Documents on Economics 104166, London School of Economics and Political Science, LSE Library.

    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:eee:stapro:v:9:y:1990:i:1:p:91-97. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.