IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v72y2007i2p141-157.html
   My bibliography  Save this article

A class of multidimensional IRT models for testing unidimensionality and clustering items

Author

Listed:
  • Francesco Bartolucci

Abstract

No abstract is available for this item.

Suggested Citation

  • Francesco Bartolucci, 2007. "A class of multidimensional IRT models for testing unidimensionality and clustering items," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 141-157, June.
  • Handle: RePEc:spr:psycho:v:72:y:2007:i:2:p:141-157
    DOI: 10.1007/s11336-005-1376-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11336-005-1376-9
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11336-005-1376-9?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. Henk Kelderman & Carl Rijkes, 1994. "Loglinear multidimensional IRT models for polytomously scored items," Psychometrika, Springer;The Psychometric Society, vol. 59(2), pages 149-176, June.
    2. Herbert Hoijtink & Meinte Vollema, 2003. "Contemporary Extensions of the Rasch Model," Quality & Quantity: International Journal of Methodology, Springer, vol. 37(3), pages 263-276, August.
    3. Ivo Molenaar, 1983. "Some improved diagnostics for failure of the Rasch model," Psychometrika, Springer;The Psychometric Society, vol. 48(1), pages 49-72, March.
    4. Francesco Bartolucci & Antonio Forcina, 2001. "Analysis of Capture-Recapture Data with a Rasch-Type Model Allowing for Conditional Dependence and Multidimensionality," Biometrics, The International Biometric Society, vol. 57(3), pages 714-719, September.
    5. Francesco Bartolucci & Antonio Forcina, 2005. "Likelihood inference on the underlying structure of IRT models," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 31-43, March.
    6. David Thissen, 1982. "Marginal maximum likelihood estimation for the one-parameter logistic model," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 175-186, June.
    7. Werner Stegelmann, 1983. "Expanding the rasch model to a general model having more than one dimension," Psychometrika, Springer;The Psychometric Society, vol. 48(2), pages 259-267, June.
    8. Hendrikus Kelderman, 1984. "Loglinear Rasch model tests," Psychometrika, Springer;The Psychometric Society, vol. 49(2), pages 223-245, June.
    9. Karl Christensen & Jakob Bjorner & Svend Kreiner & Jørgen Petersen, 2002. "Testing unidimensionality in polytomous Rasch models," Psychometrika, Springer;The Psychometric Society, vol. 67(4), pages 563-574, December.
    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. Thorsten Meiser, 1996. "Loglinear Rasch models for the analysis of stability and change," Psychometrika, Springer;The Psychometric Society, vol. 61(4), pages 629-645, December.
    2. Cees Glas, 1988. "The derivation of some tests for the rasch model from the multinomial distribution," Psychometrika, Springer;The Psychometric Society, vol. 53(4), pages 525-546, December.
    3. Francesco Bartolucci & Alessio Farcomeni & Luisa Scaccia, 2017. "A Nonparametric Multidimensional Latent Class IRT Model in a Bayesian Framework," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 952-978, December.
    4. Clemens Draxler, 2018. "Bayesian conditional inference for Rasch models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 245-262, April.
    5. Svend Kreiner & Karl Christensen, 2014. "Analyses of Model Fit and Robustness. A New Look at the PISA Scaling Model Underlying Ranking of Countries According to Reading Literacy," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 210-231, April.
    6. Bartolucci, Francesco & Bacci, Silvia & Gnaldi, Michela, 2014. "MultiLCIRT: An R package for multidimensional latent class item response models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 971-985.
    7. Yuguo Chen & Dylan Small, 2005. "Exact tests for the rasch model via sequential importance sampling," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 11-30, March.
    8. Clemens Draxler, 2010. "Sample Size Determination for Rasch Model Tests," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 708-724, December.
    9. Herbert Hoijtink, 1990. "A latent trait model for dichotomous choice data," Psychometrika, Springer;The Psychometric Society, vol. 55(4), pages 641-656, December.
    10. Svend Kreiner & Karl Christensen, 2011. "Item Screening in Graphical Loglinear Rasch Models," Psychometrika, Springer;The Psychometric Society, vol. 76(2), pages 228-256, April.
    11. Jules L. Ellis & Klaas Sijtsma, 2023. "A Test to Distinguish Monotone Homogeneity from Monotone Multifactor Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 387-412, June.
    12. N. Verhelst & C. Glas, 1993. "A dynamic generalization of the Rasch model," Psychometrika, Springer;The Psychometric Society, vol. 58(3), pages 395-415, September.
    13. Jean-Benoit Hardouin, 2007. "Rasch analysis: Estimation and tests with raschtest," Stata Journal, StataCorp LP, vol. 7(1), pages 22-44, February.
    14. Cees Glas, 1999. "Modification indices for the 2-PL and the nominal response model," Psychometrika, Springer;The Psychometric Society, vol. 64(3), pages 273-294, September.
    15. Francesco Bartolucci & Ivonne Solis-Trapala, 2010. "Multidimensional Latent Markov Models in a Developmental Study of Inhibitory Control and Attentional Flexibility in Early Childhood," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 725-743, December.
    16. C. Glas & Anna Dagohoy, 2007. "A Person Fit Test For Irt Models For Polytomous Items," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 159-180, June.
    17. Li Cai, 2010. "A Two-Tier Full-Information Item Factor Analysis Model with Applications," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 581-612, December.
    18. Li Donni, P., 2010. "Risk Preference Heterogeneity And Multiple Demand For Insurance," Health, Econometrics and Data Group (HEDG) Working Papers 10/17, HEDG, c/o Department of Economics, University of York.
    19. Francesco Bartolucci & Antonio Forcina, 2005. "Likelihood inference on the underlying structure of IRT models," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 31-43, March.
    20. Danilo Fegatelli & Luca Tardella, 2013. "Improved inference on capture recapture models with behavioural effects," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(1), pages 45-66, March.

    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:72:y:2007:i:2:p:141-157. 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.