IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v55y2011i1p34-44.html
   My bibliography  Save this article

Some exact tests for manifest properties of latent trait models

Author

Listed:
  • De Gooijer, Jan G.
  • Yuan, Ao

Abstract

Item response theory is one of the modern test theories with applications in educational and psychological testing. Recent developments made it possible to characterize some desired properties in terms of a collection of manifest ones, so that hypothesis tests on these traits can, in principle, be performed. But the existing test methodology is based on asymptotic approximation, which is impractical in most applications since the required sample sizes are often unrealistically huge. To overcome this problem, a class of tests is proposed for making exact statistical inference about four manifest properties: covariances given the sum are non-positive (CSN), manifest monotonicity (MM), conditional association (CA), and vanishing conditional dependence (VCD). One major advantage is that these exact tests do not require large sample sizes. As a result, tests for CSN and MM can be routinely performed in empirical studies. For testing CA and VCD, the exact methods are still impractical in most applications, due to the unusually large number of parameters to be tested. However, exact methods are still derived for them as an exploration toward practicality. Some numerical examples with applications of the exact tests for CSN and MM are provided.

Suggested Citation

  • De Gooijer, Jan G. & Yuan, Ao, 2011. "Some exact tests for manifest properties of latent trait models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 34-44, January.
  • Handle: RePEc:eee:csdana:v:55:y:2011:i:1:p:34-44
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(10)00167-2
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. William Stout, 1987. "A nonparametric approach for assessing latent trait unidimensionality," Psychometrika, Springer;The Psychometric Society, vol. 52(4), pages 589-617, December.
    2. D. R. Cox, 1972. "The Analysis of Multivariate Binary Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 21(2), pages 113-120, June.
    3. Paul Rosenbaum, 1987. "Comparing item characteristic curves," Psychometrika, Springer;The Psychometric Society, vol. 52(2), pages 217-233, June.
    4. Noel Cressie & Paul Holland, 1983. "Characterizing the manifest probabilities of latent trait models," Psychometrika, Springer;The Psychometric Society, vol. 48(1), pages 129-141, March.
    5. Brian Junker, 1991. "Essential independence and likelihood-based ability estimation for polytomous items," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 255-278, June.
    6. Jules Ellis & Brian Junker, 1997. "Tail-measurability in monotone latent variable models," Psychometrika, Springer;The Psychometric Society, vol. 62(4), pages 495-523, December.
    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. 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.
    2. Rudy Ligtvoet, 2022. "Incomplete Tests of Conditional Association for the Assessment of Model Assumptions," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1214-1237, December.
    3. Jules Ellis, 2014. "An Inequality for Correlations in Unidimensional Monotone Latent Variable Models for Binary Variables," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 303-316, April.

    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. Rudy Ligtvoet, 2022. "Incomplete Tests of Conditional Association for the Assessment of Model Assumptions," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1214-1237, December.
    2. A. BĂ©guin & C. Glas, 2001. "MCMC estimation and some model-fit analysis of multidimensional IRT models," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 541-561, December.
    3. Edward Ip & Yuchung Wang & Paul Boeck & Michel Meulders, 2004. "Locally dependent latent trait model for polytomous responses with application to inventory of hostility," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 191-216, June.
    4. Paul Holland, 1990. "On the sampling theory roundations of item response theory models," Psychometrika, Springer;The Psychometric Society, vol. 55(4), pages 577-601, December.
    5. Ivo Molenaar, 1998. "Data, model, conclusion, doing it again," Psychometrika, Springer;The Psychometric Society, vol. 63(4), pages 315-340, December.
    6. Johan Braeken & Francis Tuerlinckx & Paul Boeck, 2007. "Copula Functions for Residual Dependency," Psychometrika, Springer;The Psychometric Society, vol. 72(3), pages 393-411, September.
    7. Mark Reiser, 1996. "Analysis of residuals for the multionmial item response model," Psychometrika, Springer;The Psychometric Society, vol. 61(3), pages 509-528, September.
    8. Wim Linden, 1998. "Stochastic order in dichotomous item response models for fixed, adaptive, and multidimensional tests," Psychometrika, Springer;The Psychometric Society, vol. 63(3), pages 211-226, September.
    9. 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.
    10. Jeanne A. Teresi & Chun Wang & Marjorie Kleinman & Richard N. Jones & David J. Weiss, 2021. "Differential Item Functioning Analyses of the Patient-Reported Outcomes Measurement Information System (PROMIS®) Measures: Methods, Challenges, Advances, and Future Directions," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 674-711, September.
    11. 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.
    12. Theo Eggen & Norman Verhelst, 2006. "Loss of Information in Estimating Item Parameters in Incomplete Designs," Psychometrika, Springer;The Psychometric Society, vol. 71(2), pages 303-322, June.
    13. Christel Faes & Marc Aerts & Helena Geys & Geert Molenberghs, 2007. "Model Averaging Using Fractional Polynomials to Estimate a Safe Level of Exposure," Risk Analysis, John Wiley & Sons, vol. 27(1), pages 111-123, February.
    14. Jules Ellis & Arnold Wollenberg, 1993. "Local homogeneity in latent trait models. A characterization of the homogeneous monotone irt model," Psychometrika, Springer;The Psychometric Society, vol. 58(3), pages 417-429, September.
    15. Bas Hemker & Klaas Sijtsma & Ivo Molenaar & Brian Junker, 1996. "Polytomous IRT models and monotone likelihood ratio of the total score," Psychometrika, Springer;The Psychometric Society, vol. 61(4), pages 679-693, December.
    16. Edward Ip, 2000. "Adjusting for information inflation due to local dependency in moderately large item clusters," Psychometrika, Springer;The Psychometric Society, vol. 65(1), pages 73-91, March.
    17. Douglas L. Steinley & M. J. Brusco, 2019. "Using an Iterative Reallocation Partitioning Algorithm to Verify Test Multidimensionality," Journal of Classification, Springer;The Classification Society, vol. 36(3), pages 397-413, October.
    18. Kromidha, Endrit & Li, Matthew C., 2019. "Determinants of leadership in online social trading: A signaling theory perspective," Journal of Business Research, Elsevier, vol. 97(C), pages 184-197.
    19. Kim, Chul & Jun, Duk Bin & Park, Sungho, 2018. "Capturing flexible correlations in multiple-discrete choice outcomes using copulas," International Journal of Research in Marketing, Elsevier, vol. 35(1), pages 34-59.
    20. Francesco Bartolucci & Claudia Pigini, 2018. "Partial effects estimation for fixed-effects logit panel data models," Working Papers 431, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.

    More about this item

    Keywords

    Conditional distribution Exact test Monte Carlo Markov chain Monte Carlo;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    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:eee:csdana:v:55:y:2011:i:1:p:34-44. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    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.