IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v52y1987i3p431-462.html
   My bibliography  Save this article

On structural equation modeling with data that are not missing completely at random

Author

Listed:
  • Bengt Muthén
  • David Kaplan
  • Michael Hollis

Abstract

No abstract is available for this item.

Suggested Citation

  • Bengt Muthén & David Kaplan & Michael Hollis, 1987. "On structural equation modeling with data that are not missing completely at random," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 431-462, September.
    • Handle: RePEc:spr:psycho:v:52:y:1987:i:3:p:431-462
    DOI: 10.1007/BF02294365
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02294365
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02294365?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. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    2. C. Hendricks Brown, 1983. "Asymptotic comparison of missing data procedures for estimating factor loadings," Psychometrika, Springer;The Psychometric Society, vol. 48(2), pages 269-291, June.
    3. R. Bock & Murray Aitkin, 1981. "Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 443-459, December.
    4. Little, Roderick J A, 1985. "A Note about Models for Selectivity Bias," Econometrica, Econometric Society, vol. 53(6), pages 1469-1474, November.
    5. K. Jöreskog, 1969. "A general approach to confirmatory maximum likelihood factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 34(2), pages 183-202, June.
    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. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Incomplete panels and selection bias : A survey," Discussion Paper 1992-7, Tilburg University, Center for Economic Research.
    2. Angrist, Joshua D., 1997. "Conditional independence in sample selection models," Economics Letters, Elsevier, vol. 54(2), pages 103-112, February.
    3. P. Bentler, 1986. "Structural modeling and psychometrika: An historical perspective on growth and achievements," Psychometrika, Springer;The Psychometric Society, vol. 51(1), pages 35-51, March.
    4. Boehm, Martin, 2008. "Determining the impact of internet channel use on a customer's lifetime," Journal of Interactive Marketing, Elsevier, vol. 22(3), pages 2-22.
    5. Joshua D. Angrist, 1995. "Conditioning on the Probability of Selection to Control Selection Bias," NBER Technical Working Papers 0181, National Bureau of Economic Research, Inc.
    6. Norman Rose & Matthias Davier & Benjamin Nagengast, 2017. "Modeling Omitted and Not-Reached Items in IRT Models," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 795-819, September.
    7. Wesley R. Hartmann, 2006. "—Comment on Structural Modeling in Marketing: Review and Assessment," Marketing Science, INFORMS, vol. 25(6), pages 620-621, 11-12.
    8. Patrick Puhani, 2000. "The Heckman Correction for Sample Selection and Its Critique," Journal of Economic Surveys, Wiley Blackwell, vol. 14(1), pages 53-68, February.
    9. Denis Conniffe & Vanessa Gash & Philip J., 2000. "Evaluating Programmes: Experiments, Non-Experiments and Propensity Scores," Papers WP126, Economic and Social Research Institute (ESRI).
    10. Yeh Jason Jia-Hsing, 2009. "Missing (Completely?) At Random: Lessons from Insurance Studies," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 3(2), pages 1-13, April.
    11. Wu, I-Ding & Hand, David J., 2007. "Handling selection bias when choosing actions in retail credit applications," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1560-1568, December.
    12. A. Arrighetti & R. Brancati & A. Lasagni & A. Maresca, 2015. "Firms’ heterogeneity and performance in manufacturing during the great recession," Economics Department Working Papers 2015-EP03, Department of Economics, Parma University (Italy).
    13. Alessandra Mattei & Fabrizia Mealli & Barbara Pacini, 2014. "Identification of causal effects in the presence of nonignorable missing outcome values," Biometrics, The International Biometric Society, vol. 70(2), pages 278-288, June.
    14. Jiwei Zhang & Zhaoyuan Zhang & Jian Tao, 2021. "A Bayesian algorithm based on auxiliary variables for estimating GRM with non-ignorable missing data," Computational Statistics, Springer, vol. 36(4), pages 2643-2669, December.
    15. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Incomplete panels and selection bias : A survey," Other publications TiSEM 65401dae-613b-4e10-a8ae-c, Tilburg University, School of Economics and Management.
    16. Robert Gibbons & Donald Hedeker, 1992. "Full-information item bi-factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 57(3), pages 423-436, September.
    17. P. M. Bentler & Chih-Ping Chou, 1987. "Practical Issues in Structural Modeling," Sociological Methods & Research, , vol. 16(1), pages 78-117, August.
    18. Sènakpon Fidèle A. Dedehouanou & Luca Tiberti & Hilaire G. Houeninvo & Djohodo Inès Monwanou, 2019. "Working while studying: Employment premium or penalty for youth in Benin?," Working Papers PMMA 2019-03, PEP-PMMA.
    19. Sandra Müllbacher & Wolfgang Nagl, 2017. "Labour supply in Austria: an assessment of recent developments and the effects of a tax reform," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(3), pages 465-486, August.
    20. Insoo Cho & Peter F. Orazem, 2021. "How endogenous risk preferences and sample selection affect analysis of firm survival," Small Business Economics, Springer, vol. 56(4), pages 1309-1332, April.

    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:52:y:1987:i:3:p:431-462. 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.