IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v29y2001i4p468-508.html
   My bibliography  Save this article

Improper Solutions in Structural Equation Models

Author

Listed:
  • FEINIAN CHEN

    (University of North Carolina at Chapel Hill)

  • KENNETH A. BOLLEN

    (University of North Carolina at Chapel Hill)

  • PAMELA PAXTON

    (Ohio State University)

  • PATRICK J. CURRAN

    (University of North Carolina at Chapel Hill)

  • JAMES B. KIRBY

    (Agency for Healthcare Research and Quality)

Abstract

In this article, the authors examine the most common type of improper solutions: zero or negative error variances. They address the causes of, consequences of, and strategies to handle these issues. Several hypotheses are evaluated using Monte Carlo simulation models, including two structural equation models with several misspecifications of each model. Results suggested several unique findings. First, increasing numbers of omitted paths in the measurement model were associated with decreasing numbers of improper solutions. Second, bias in the parameter estimates was higher in samples with improper solutions than in samples including only proper solutions. Third, investigations of the consequences of using constrained estimates in the presence of improper solutions indicated that inequality constraints helped some samples achieve convergence. Finally, the use of confidence intervals as well as four other proposed tests yielded similar results when testing whether the error variance was greater than or equal to zero.

Suggested Citation

  • Feinian Chen & Kenneth A. Bollen & Pamela Paxton & Patrick J. Curran & James B. Kirby, 2001. "Improper Solutions in Structural Equation Models," Sociological Methods & Research, , vol. 29(4), pages 468-508, May.
    • Handle: RePEc:sae:somere:v:29:y:2001:i:4:p:468-508
    DOI: 10.1177/0049124101029004003
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124101029004003
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124101029004003?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. Albert Satorra, 1990. "Robustness issues in structural equation modeling: a review of recent developments," Quality & Quantity: International Journal of Methodology, Springer, vol. 24(4), pages 367-386, November.
    2. David Gerbing & James Anderson, 1987. "Improper solutions in the analysis of covariance structures: Their interpretability and a comparison of alternate respecifications," Psychometrika, Springer;The Psychometric Society, vol. 52(1), pages 99-111, March.
    3. Otto Driel, 1978. "On various causes of improper solutions in maximum likelihood factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 43(2), pages 225-243, June.
    4. Albert Satorra & Willem Saris, 1985. "Power of the likelihood ratio test in covariance structure analysis," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 83-90, March.
    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. Reinartz, Werner & Haenlein, Michael & Henseler, Jörg, 2009. "An empirical comparison of the efficacy of covariance-based and variance-based SEM," International Journal of Research in Marketing, Elsevier, vol. 26(4), pages 332-344.

    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. Kenneth A. Bollen & James B. Kirby & Patrick J. Curran & Pamela M. Paxton & Feinian Chen, 2007. "Latent Variable Models Under Misspecification: Two-Stage Least Squares (2SLS) and Maximum Likelihood (ML) Estimators," Sociological Methods & Research, , vol. 36(1), pages 48-86, August.
    2. Kohei Adachi, 2013. "Factor Analysis with EM Algorithm Never Gives Improper Solutions when Sample Covariance and Initial Parameter Matrices Are Proper," Psychometrika, Springer;The Psychometric Society, vol. 78(2), pages 380-394, April.
    3. Stanislav Kolenikov & Kenneth A. Bollen, 2012. "Testing Negative Error Variances," Sociological Methods & Research, , vol. 41(1), pages 124-167, February.
    4. Julia Grass & Florian Krieger & Philipp Paulus & Samuel Greiff & Anja Strobel & Alexander Strobel, 2019. "Thinking in action: Need for Cognition predicts Self-Control together with Action Orientation," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-20, August.
    5. Alberto Maydeu-Olivares & Rosa Montaño, 2013. "How Should We Assess the Fit of Rasch-Type Models? Approximating the Power of Goodness-of-Fit Statistics in Categorical Data Analysis," Psychometrika, Springer;The Psychometric Society, vol. 78(1), pages 116-133, January.
    6. 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.
    7. Eric V. Bindah & Nor Othman, 2013. "Refining and Validating a Family Communication Measure Using Exploratory and Confirmatory Factor Analysis," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 3(1), pages 168-186, January.
    8. Ke-Hai Yuan & Wai Chan, 2005. "On Nonequivalence of Several Procedures of Structural Equation Modeling," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 791-798, December.
    9. Ke-Hai Yuan & Ying Cheng & Wei Zhang, 2010. "Determinants of Standard Errors of MLEs in Confirmatory Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 633-648, December.
    10. Wolfgang Jagodzinski & Steffen M. Kãœhnel & Peter Schmidt, 1987. "Is there a “Socratic Effect†in Nonexperimental Panel Studies?," Sociological Methods & Research, , vol. 15(3), pages 259-302, February.
    11. Sophie Hentschel & Michael Eid & Tanja Kutscher, 2017. "The Influence of Major Life Events and Personality Traits on the Stability of Affective Well-Being," Journal of Happiness Studies, Springer, vol. 18(3), pages 719-741, June.
    12. Roderick McDonald, 1986. "Describing the elephant: Structure and function in multivariate data," Psychometrika, Springer;The Psychometric Society, vol. 51(4), pages 513-534, December.
    13. Stanislav Kolenikov, 2009. "Confirmatory factor analysis using confa," Stata Journal, StataCorp LP, vol. 9(3), pages 329-373, September.
    14. Ke-Hai Yuan & Peter Bentler, 2006. "Mean Comparison: Manifest Variable Versus Latent Variable," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 139-159, March.
    15. Willem E. Saris, 2001. "The Strength of the Causal Relationship between Living Conditions and Satisfaction," Sociological Methods & Research, , vol. 30(1), pages 11-34, August.
    16. Germà Coenders & Joan Batista-Foguet & Willem Saris, 2008. "Simple, Efficient and Distribution-free Approach to Interaction Effects in Complex Structural Equation Models," Quality & Quantity: International Journal of Methodology, Springer, vol. 42(3), pages 369-396, June.
    17. 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.
    18. Ringle, Christian M. & Götz, Oliver & Wetzels, Martin & Wilson, Bradley, 2009. "On the Use of Formative Measurement Specifications in Structural Equation Modeling: A Monte Carlo Simulation Study to Compare Covariance-Based and Partial Least Squares Model Estimation Methodologies," MPRA Paper 15390, University Library of Munich, Germany.
    19. Jonathan P Tennant & Norman MacLeod, 2014. "Snout Shape in Extant Ruminants," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-13, November.
    20. Junya Kumagai & Mihoko Wakamatsu & Shunsuke Managi, 2021. "Do commuters adapt to in-vehicle crowding on trains?," Transportation, Springer, vol. 48(5), pages 2357-2399, October.

    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:29:y:2001:i:4:p:468-508. 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.