IDEAS home Printed from https://ideas.repec.org/a/spr/qualqt/v35y2001i2p161-171.html

The Relationship of the Degree of Exposure to a Technological Disaster and Emotional Response: A Structural Model Approach

Author

Listed:
  • Adolfo Esparcia
  • Joan Guárdia Olmos

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:qualqt:v:35:y:2001:i:2:p:161-171
    DOI: 10.1023/A:1010364325879
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1010364325879
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1023/A:1010364325879?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Wai-Yin Poon & Sik-Yum Lee, 1987. "Maximum likelihood estimation of multivariate polyserial and polychoric correlation coefficients," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 409-430, September.
    2. Albert Satorra, 1989. "Alternative test criteria in covariance structure analysis: A unified approach," Psychometrika, Springer;The Psychometric Society, vol. 54(1), pages 131-151, March.
    3. 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.
    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. 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.
    2. 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.
    3. 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.
    4. 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.
    5. de Leon, A.R., 2005. "Pairwise likelihood approach to grouped continuous model and its extension," Statistics & Probability Letters, Elsevier, vol. 75(1), pages 49-57, November.
    6. A. R. de Leon & A. Soo & T. Williamson, 2011. "Classification with discrete and continuous variables via general mixed-data models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(5), pages 1021-1032, February.
    7. Ting Wang & Edgar C. Merkle & Achim Zeileis, 2013. "Score-Based Tests of Measurement Invariance: Use in Practice," Working Papers 2013-33, Faculty of Economics and Statistics, Universität Innsbruck.
    8. 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.
    9. Po-Hsien Huang, 2017. "Asymptotics of AIC, BIC, and RMSEA for Model Selection in Structural Equation Modeling," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 407-426, June.
    10. Piotr Tarka, 2018. "An overview of structural equation modeling: its beginnings, historical development, usefulness and controversies in the social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 313-354, January.
    11. Albert Satorra & Heinz Neudecker, 2015. "A Theorem on the Rank of a Product of Matrices with Illustration of Its Use in Goodness of Fit Testing," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 938-948, December.
    12. Hao Bai & Yuan Zhong & Xin Gao & Wei Xu, 2020. "Multivariate Mixed Response Model with Pairwise Composite-Likelihood Method," Stats, MDPI, vol. 3(3), pages 1-18, July.
    13. Robert Jennrich & Albert Satorra, 2014. "The Nonsingularity of Γ in Covariance Structure Analysis of Nonnormal Data," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 51-59, January.
    14. Yutaka Kano & Masamori Ihara, 1994. "Identification of inconsistent variates in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 59(1), pages 5-20, March.
    15. 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.
    16. Jonas Moss & Steffen Grønneberg, 2023. "Partial Identification of Latent Correlations with Ordinal Data," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 241-252, March.
    17. Albert Satorra, 1991. "Asymptotic robust inferences in the analysis of mean and covariance structures," Economics Working Papers 3, Department of Economics and Business, Universitat Pompeu Fabra.
    18. Leila Amiri & Mojtaba Khazaei & Mojtaba Ganjali, 2018. "A mixture latent variable model for modeling mixed data in heterogeneous populations and its applications," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(1), pages 95-115, January.
    19. Hikaru Hasegawa, 2013. "On polychoric and polyserial partial correlation coefficients: a Bayesian approach," METRON, Springer;Sapienza Università di Roma, vol. 71(2), pages 139-156, September.
    20. Haruhiko Ogasawara, 2001. "Standard errors of fit indices using residuals in structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 66(3), pages 421-436, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:spr:qualqt:v:35:y:2001:i:2:p:161-171. 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.