IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v66y2001i3p357-371.html
   My bibliography  Save this article

Identifiability of nonlinear logistic test models

Author

Listed:
  • Timo Bechger
  • Norman Verhelst
  • Huub Verstralen

Abstract

No abstract is available for this item.

Suggested Citation

  • Timo Bechger & Norman Verhelst & Huub Verstralen, 2001. "Identifiability of nonlinear logistic test models," Psychometrika, Springer;The Psychometric Society, vol. 66(3), pages 357-371, September.
    • Handle: RePEc:spr:psycho:v:66:y:2001:i:3:p:357-371
    DOI: 10.1007/BF02294439
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02294439
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02294439?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. Bekker, Paul A., 1989. "Identification in restricted factor models and the evaluation of rank conditions," Journal of Econometrics, Elsevier, vol. 41(1), pages 5-16, May.
    2. Gabrielsen, Arne, 1978. "Consistency and identifiability," Journal of Econometrics, Elsevier, vol. 8(2), pages 261-263, October.
    3. René Butter & Paul Boeck & Norman Verhelst, 1998. "An item response model with internal restrictions on item difficulty," Psychometrika, Springer;The Psychometric Society, vol. 63(1), pages 47-63, 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. Ernesto San Martín & Alejandro Jara & Jean-Marie Rolin & Michel Mouchart, 2011. "On the Bayesian Nonparametric Generalization of IRT-Type Models," Psychometrika, Springer;The Psychometric Society, vol. 76(3), pages 385-409, July.
    2. Timo Bechger & Huub Verstralen & Norman Verhelst & Gunter Maris, 2004. "Equivalent LLTMS: A rejoinder," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 317-318, June.
    3. Gunter Maris & Timo Bechger, 2004. "Equivalent MIRID models," Psychometrika, Springer;The Psychometric Society, vol. 69(4), pages 627-639, December.
    4. Wim J. Linden & Michelle D. Barrett, 2016. "Linking Item Response Model Parameters," Psychometrika, Springer;The Psychometric Society, vol. 81(3), pages 650-673, September.

    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. Wai Chan & Peter M. Bentler, 1993. "The Covariance Structure Analysis of Ipsative Data," Sociological Methods & Research, , vol. 22(2), pages 214-247, November.
    2. Sentana, Enrique & Fiorentini, Gabriele, 2001. "Identification, estimation and testing of conditionally heteroskedastic factor models," Journal of Econometrics, Elsevier, vol. 102(2), pages 143-164, June.
    3. Gerhard Fischer, 2004. "Remarks on “equivalent linear logistic test models” by Bechger, Verstralen, and Verhelst (2002)," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 305-315, June.
    4. Sylvia Frühwirth-Schnatter & Darjus Hosszejni & Hedibert Freitas Lopes, 2023. "When It Counts—Econometric Identification of the Basic Factor Model Based on GLT Structures," Econometrics, MDPI, vol. 11(4), pages 1-30, November.
    5. Timo Bechger & Huub Verstralen & Norman Verhelst & Gunter Maris, 2004. "Equivalent LLTMS: A rejoinder," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 317-318, June.
    6. Gabriele Fiorentini & Enrique Sentana, 2012. "Tests for Serial Dependence in Static, Non-Gaussian Factor Models," Working Papers wp2012_1211, CEMFI.
    7. Peter Molenaar & Jan Gooijer & Bernhard Schmitz, 1992. "Dynamic factor analysis of nonstationary multivariate time series," Psychometrika, Springer;The Psychometric Society, vol. 57(3), pages 333-349, September.
    8. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests for Static Factor Models," Working Papers wp2009_0912, CEMFI.
    9. Tom Holden, 2012. "Learning from learners," School of Economics Discussion Papers 1512, School of Economics, University of Surrey.
    10. Ernesto Martín & Jorge González & Francis Tuerlinckx, 2015. "On the Unidentifiability of the Fixed-Effects 3PL Model," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 450-467, June.
    11. George Halkos & Kyriaki Tsilika, 2015. "Programming Identification Criteria in Simultaneous Equation Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 157-170, June.
    12. Timo Bechger & Gunter Maris, 2015. "A Statistical Test for Differential Item Pair Functioning," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 317-340, June.
    13. Terence Reilly, 1995. "A Necessary and Sufficient Condition for Identification of Confirmatory Factor Analysis Models of Factor Complexity One," Sociological Methods & Research, , vol. 23(4), pages 421-441, May.
    14. P. Bentler & David Weeks, 1980. "Linear structural equations with latent variables," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 289-308, September.
    15. Wegge, Leon L., 1996. "Local identifiability of the factor analysis and measurement error model parameter," Journal of Econometrics, Elsevier, vol. 70(2), pages 351-382, February.
    16. Ernesto San Martín & Jean-Marie Rolin & Luis Castro, 2013. "Identification of the 1PL Model with Guessing Parameter: Parametric and Semi-parametric Results," Psychometrika, Springer;The Psychometric Society, vol. 78(2), pages 341-379, April.
    17. Wim J. Linden & Michelle D. Barrett, 2016. "Linking Item Response Model Parameters," Psychometrika, Springer;The Psychometric Society, vol. 81(3), pages 650-673, September.
    18. Sylvia Fruhwirth-Schnatter & Darjus Hosszejni & Hedibert Freitas Lopes, 2023. "When it counts -- Econometric identification of the basic factor model based on GLT structures," Papers 2301.06354, arXiv.org.
    19. Justin L. Kern & Steven Andrew Culpepper, 2020. "A Restricted Four-Parameter IRT Model: The Dyad Four-Parameter Normal Ogive (Dyad-4PNO) Model," Psychometrika, Springer;The Psychometric Society, vol. 85(3), pages 575-599, September.
    20. S. Rabe-Hesketh & A. Skrondal, 2001. "Parameterization of Multivariate Random Effects Models for Categorical Data," Biometrics, The International Biometric Society, vol. 57(4), pages 1256-1263, December.

    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:66:y:2001:i:3:p:357-371. 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.