IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v26y1998i3p329-367.html

Robustness Studies in Covariance Structure Modeling

Author

Listed:
  • JEFFREY J. HOOGLAND

    (University of Groningen)

  • ANNE BOOMSMA

    (University of Groningen)

Abstract

In covariance structure modeling, several estimation methods are available. The robustness of an estimator against specific violations of assumptions can be determined empirically by means of a Monte Carlo study. Many such studies in covariance structure analysis have been published, but the conclusions frequently seem to contradict each other. An overview of robustness studies in covariance structure analysis is given, and an attempt is made to generalize findings. Robustness studies are described and distinguished from each other systematically by means of certain characteristics. These characteristics serve as explanatory variables in a meta-analysis concerning the behavior of parameter estimators, standard error estimators, and goodness-of-fit statistics when the model is correctly specified.

Suggested Citation

  • Jeffrey J. Hoogland & Anne Boomsma, 1998. "Robustness Studies in Covariance Structure Modeling," Sociological Methods & Research, , vol. 26(3), pages 329-367, February.
    • Handle: RePEc:sae:somere:v:26:y:1998:i:3:p:329-367
    DOI: 10.1177/0049124198026003003
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124198026003003
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124198026003003?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. Kenneth Bollen, 1996. "An alternative two stage least squares (2SLS) estimator for latent variable equations," Psychometrika, Springer;The Psychometric Society, vol. 61(1), pages 109-121, March.
    2. C. Vale & Vincent Maurelli, 1983. "Simulating multivariate nonnormal distributions," Psychometrika, Springer;The Psychometric Society, vol. 48(3), pages 465-471, September.
    3. P. Bentler & David Weeks, 1980. "Linear structural equations with latent variables," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 289-308, September.
    4. Jeri Benson & John Fleishman, 1994. "The robustness of maximum likelihood and distribution-free estimators to non-normality in confirmatory factor analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 28(2), pages 117-136, May.
    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. Scheiner, Joachim, 2010. "Social inequalities in travel behaviour: trip distances in the context of residential self-selection and lifestyles," Journal of Transport Geography, Elsevier, vol. 18(6), pages 679-690.
    2. Kees van Montfort & Ab Mooijaart & Frits Meijerink, 2009. "Estimating structural equation models with non‐normal variables by using transformations," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(2), pages 213-226, May.
    3. Ivo Molenaar, 1998. "Data, model, conclusion, doing it again," Psychometrika, Springer;The Psychometric Society, vol. 63(4), pages 315-340, December.
    4. van den Broek, Karlijn L. & Walker, Ian & Klöckner, Christian A., 2019. "Drivers of energy saving behaviour: The relative influence of intentional, normative, situational and habitual processes," Energy Policy, Elsevier, vol. 132(C), pages 811-819.
    5. Bügel, Marnix S. & Verhoef, Peter C. & Buunk, Abraham P., 2011. "Customer intimacy and commitment to relationships with firms in five different sectors: Preliminary evidence," Journal of Retailing and Consumer Services, Elsevier, vol. 18(4), pages 247-258.
    6. Nikodem Szumilo & Edyta Laszkiewicz & Franz Fuerst, 2017. "The spatial impact of employment centres on housing markets," Spatial Economic Analysis, Taylor & Francis Journals, vol. 12(4), pages 472-491, October.
    7. So Yeon Chun & Michael W. Browne & Alexander Shapiro, 2018. "Modified Distribution-Free Goodness-of-Fit Test Statistic," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 48-66, March.
    8. Ory, David T, 2007. "Structural Equation Modeling of Relative Desired Travel Amounts," Institute of Transportation Studies, Working Paper Series qt8mj659fp, Institute of Transportation Studies, UC Davis.
    9. Ory, David Terrance, 2007. "Structural Equation Modeling of Relative Desired Travel Amounts," University of California Transportation Center, Working Papers qt7rb3x52m, University of California Transportation Center.
    10. Daniel McNeish, 2017. "Missing data methods for arbitrary missingness with small samples," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(1), pages 24-39, January.
    11. Paul Dudgeon, 2017. "Some Improvements in Confidence Intervals for Standardized Regression Coefficients," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 928-951, December.

    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. Pasquale Dolce & Natale Lauro, 2015. "Comparing maximum likelihood and PLS estimates for structural equation modeling with formative blocks," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 891-902, May.
    2. Theo Dijkstra & Karin Schermelleh-Engel, 2014. "Consistent Partial Least Squares for Nonlinear Structural Equation Models," Psychometrika, Springer;The Psychometric Society, vol. 79(4), pages 585-604, October.
    3. Steven Andrew Culpepper & Herman Aguinis & Justin L. Kern & Roger Millsap, 2019. "High-Stakes Testing Case Study: A Latent Variable Approach for Assessing Measurement and Prediction Invariance," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 285-309, March.
    4. Hangeun Lee & Seong Ho Lee, 2019. "The Impact of Corporate Social Responsibility on Long-Term Relationships in the Business-to-Business Market," Sustainability, MDPI, vol. 11(19), pages 1-12, September.
    5. Enno Siemsen & Kenneth A. Bollen, 2007. "Least Absolute Deviation Estimation in Structural Equation Modeling," Sociological Methods & Research, , vol. 36(2), pages 227-265, November.
    6. 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.
    7. 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.
    8. M Hashem Pesaran & Takashi Yamagata, 2024. "Testing for Alpha in Linear Factor Pricing Models with a Large Number of Securities," Journal of Financial Econometrics, Oxford University Press, vol. 22(2), pages 407-460.
    9. Prianto Budi Saptono & Gustofan Mahmud & Intan Pratiwi & Dwi Purwanto & Ismail Khozen & Lambang Wiji Imantoro & Maria Eurelia Wayan, 2024. "Book-Tax Differences during the Crisis: Does Corporate Social Responsibility Matter?," Sustainability, MDPI, vol. 16(17), pages 1-38, August.
    10. Ann Majchrzak & Arvind Malhotra & Richard John, 2005. "Perceived Individual Collaboration Know-How Development Through Information Technology–Enabled Contextualization: Evidence from Distributed Teams," Information Systems Research, INFORMS, vol. 16(1), pages 9-27, March.
    11. Pesaran, M. Hashem & Yamagata, Takashi, 2012. "Testing CAPM with a Large Number of Assets," IZA Discussion Papers 6469, Institute of Labor Economics (IZA).
    12. Junmin Lee & Keungoui Kim & Hyunha Shin & Junseok Hwang, 2018. "Acceptance Factors of Appropriate Technology: Case of Water Purification Systems in Binh Dinh, Vietnam," Sustainability, MDPI, vol. 10(7), pages 1-20, June.
    13. Gary van Vuuren & Riaan de Jongh, 2017. "A comparison of risk aggregation estimates using copulas and Fleishman distributions," Applied Economics, Taylor & Francis Journals, vol. 49(17), pages 1715-1731, April.
    14. Kenneth Bollen & Stanislav Kolenikov & Shawn Bauldry, 2014. "Model-Implied Instrumental Variable—Generalized Method of Moments (MIIV-GMM) Estimators for Latent Variable Models," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 20-50, January.
    15. Nagahara, Yuichi, 2004. "A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 1-29, August.
    16. Wiebke Kuklys, 2004. "Measuring Standard of Living in the UK - An Application of Sen's Functioning Approach Using Structural Equation Models," Papers on Strategic Interaction 2004-11, Max Planck Institute of Economics, Strategic Interaction Group.
    17. Ke-Hai Yuan & Peter Bentler, 2002. "On robusiness of the normal-theory based asymptotic distributions of three reliability coefficient estimates," Psychometrika, Springer;The Psychometric Society, vol. 67(2), pages 251-259, June.
    18. Alejandro Díaz-Bautista & Diego Prieto Seyffert & Luis Treviño Garza, 2004. "La Política Monetaria y el Corto en México," Macroeconomics 0402023, University Library of Munich, Germany.
    19. Tsonaka, R. & Moustaki, I., 2007. "Parameter constraints in generalized linear latent variable models," Computational Statistics & Data Analysis, Elsevier, vol. 51(9), pages 4164-4177, May.

    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:26:y:1998:i:3:p:329-367. 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.