IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v57y1992i1p89-105.html
   My bibliography  Save this article

Structural equation models with continuous and polytomous variables

Author

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

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:psycho:v:57:y:1992:i:1:p:89-105
    DOI: 10.1007/BF02294660
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02294660
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02294660?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Ulf Olsson & Fritz Drasgow & Neil Dorans, 1982. "The polyserial correlation coefficient," Psychometrika, Springer;The Psychometric Society, vol. 47(3), pages 337-347, September.
    2. Sik-Yum Lee & Wai-Yin Poon, 1986. "Maximum likelihood estimation of polyserial correlations," Psychometrika, Springer;The Psychometric Society, vol. 51(1), pages 113-121, March.
    3. Satorra, Albert & Bentler, Peter M., 1990. "Model conditions for asymptotic robustness in the analysis of linear relations," Computational Statistics & Data Analysis, Elsevier, vol. 10(3), pages 235-249, December.
    4. 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.
    5. Anders Christoffersson, 1975. "Factor analysis of dichotomized variables," Psychometrika, Springer;The Psychometric Society, vol. 40(1), pages 5-32, 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. 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. Irini Moustaki & Martin Knott, 2000. "Generalized latent trait models," Psychometrika, Springer;The Psychometric Society, vol. 65(3), pages 391-411, September.
    3. Kenneth Bollen & David Guilkey & Thomas Mroz, 1995. "Binary outcomes and endogenous explanatory variables: Tests and solutions with an application to the demand for contraceptive use in tunisia," Demography, Springer;Population Association of America (PAA), vol. 32(1), pages 111-131, February.
    4. Evan Munro & Serena Ng, 2022. "Latent Dirichlet Analysis of Categorical Survey Responses," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 256-271, January.
    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. Willem Heiser, 2004. "Geometric representation of association between categories," Psychometrika, Springer;The Psychometric Society, vol. 69(4), pages 513-545, December.
    8. Martin Spiess, 2000. "A Generalized Estimating/Pseudo-Score Equations Approach for the Estimation of Structural Equation Models," Discussion Papers of DIW Berlin 218, DIW Berlin, German Institute for Economic Research.
    9. Xin-Yuan Song & Sik-Yum Lee, 2002. "Analysis of structural equation model with ignorable missing continuous and polytomous data," Psychometrika, Springer;The Psychometric Society, vol. 67(2), pages 261-288, June.
    10. 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.
    11. 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.
    12. Lee, Sik-Yum & Song, Xin-Yuan, 2003. "Maximum likelihood estimation and model comparison of nonlinear structural equation models with continuous and polytomous variables," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 125-142, October.
    13. Mitchell, James & Weale, Martin R., 2007. "The rationality and reliability of expectations reported by British households: micro evidence from the British household panel survey," Discussion Paper Series 1: Economic Studies 2007,19, Deutsche Bundesbank.
    14. 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.
    15. 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.

    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. 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. 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.
    3. Ventura, Eva & Satorra, Albert, 2015. "A multiple indicator model for panel data: an application to ICT area-level variation," 26th European Regional ITS Conference, Madrid 2015 127191, International Telecommunications Society (ITS).
    4. Yang Yixin & Lü Xin & Ma Jian & Qiao Han, 2014. "A Robust Factor Analysis Model for Dichotomous Data," Journal of Systems Science and Information, De Gruyter, vol. 2(5), pages 437-450, October.
    5. Golob, Thomas F. & Recker, Wilfred W. & Alvarez, Veronica M., 2004. "Safety aspects of freeway weaving sections," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(1), pages 35-51, January.
    6. 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.
    7. Ke-Hai Yuan & Yubin Tian & Hirokazu Yanagihara, 2015. "Empirical Correction to the Likelihood Ratio Statistic for Structural Equation Modeling with Many Variables," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 379-405, June.
    8. Haj-Salem, Narjes & Chebat, Jean Charles & Michon, Richard & Oliveira, Sandra, 2016. "Why male and female shoppers do not see mall loyalty through the same lens? The mediating role of self-congruity," Journal of Business Research, Elsevier, vol. 69(3), pages 1219-1227.
    9. Kano, Yutaka & Takai, Keiji, 2011. "Analysis of NMAR missing data without specifying missing-data mechanisms in a linear latent variate model," Journal of Multivariate Analysis, Elsevier, vol. 102(9), pages 1241-1255, October.
    10. Skinner, Chris J., 2018. "Analysis of categorical data for complex surveys," LSE Research Online Documents on Economics 89707, London School of Economics and Political Science, LSE Library.
    11. Richard L. Dukes & Jodie B . Ullman & Judith A. Stein, 1996. "Three-Year Follow-Up of Drug Abuse Resistance Education (D.A.R.E.)," Evaluation Review, , vol. 20(1), pages 49-66, February.
    12. Wu, Jianmin & Bentler, Peter M., 2013. "Limited information estimation in binary factor analysis: A review and extension," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 392-403.
    13. Steffen Grønneberg & Jonas Moss & Njål Foldnes, 2020. "Partial Identification of Latent Correlations with Binary Data," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 1028-1051, December.
    14. 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.
    15. Haruhiko Ogasawara, 2004. "Asymptotic biases in exploratory factor analysis and structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 235-256, June.
    16. Dylan Molenaar, 2015. "Heteroscedastic Latent Trait Models for Dichotomous Data," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 625-644, September.
    17. Robert Cudeck & Kelli Klebe & Susan Henly, 1993. "A simple Gauss-Newton procedure for covariance structure analysis with high-level computer languages," Psychometrika, Springer;The Psychometric Society, vol. 58(2), pages 211-232, June.
    18. Robert O'Brien & Pamela Homer, 1987. "Corrections for coarsely categorized measures: LISREL's polyserial and polychoric correlations," Quality & Quantity: International Journal of Methodology, Springer, vol. 21(4), pages 349-360, December.
    19. 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.
    20. Dr Martin Weale & Dr. James Mitchell, 2007. "The Rationality and Reliability of Expectations Reported by British Households: Micro Evidence from the British Household Panel Survey," National Institute of Economic and Social Research (NIESR) Discussion Papers 287, National Institute of Economic and Social Research.

    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:psycho:v:57:y:1992:i:1:p:89-105. 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.