IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v61y1996i1p41-71.html
   My bibliography  Save this article

Marginal maximum likelihood estimation for a psychometric model of discontinuous development

Author

Listed:
  • Robert Mislevy
  • Mark Wilson

Abstract

No abstract is available for this item.

Suggested Citation

  • Robert Mislevy & Mark Wilson, 1996. "Marginal maximum likelihood estimation for a psychometric model of discontinuous development," Psychometrika, Springer;The Psychometric Society, vol. 61(1), pages 41-71, March.
    • Handle: RePEc:spr:psycho:v:61:y:1996:i:1:p:41-71
    DOI: 10.1007/BF02296958
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02296958
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02296958?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. J. Ramsay, 1975. "Solving implicit equations in psychometric data analysis," Psychometrika, Springer;The Psychometric Society, vol. 40(3), pages 337-360, September.
    2. Robert Mislevy, 1984. "Estimating latent distributions," Psychometrika, Springer;The Psychometric Society, vol. 49(3), pages 359-381, September.
    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. Richard McHugh, 1956. "Efficient estimation and local identification in latent class analysis," Psychometrika, Springer;The Psychometric Society, vol. 21(4), pages 331-347, December.
    5. Henk Kelderman, 1989. "Item bias detection using loglinear irt," Psychometrika, Springer;The Psychometric Society, vol. 54(4), pages 681-697, September.
    6. Keam-Claude Falmagne, 1989. "A latent trait theory via a stochastic learning theory for a knowledge space," Psychometrika, Springer;The Psychometric Society, vol. 54(2), pages 283-303, June.
    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. Meredith Langi & Minjeong Jeon, 2023. "Identifying and Supporting Academically Low-Performing Schools in a Developing Country: An Application of a Specialized Multilevel IRT Model to PISA-D Assessment Data," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 332-356, March.
    2. Frank Rijmen & Paul Boeck & Han Maas, 2005. "An IRT Model with a Parameter-Driven Process for Change," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 651-669, December.
    3. Mark Wilson, 2013. "Seeking a Balance Between the Statistical and Scientific Elements in Psychometrics," Psychometrika, Springer;The Psychometric Society, vol. 78(2), pages 211-236, April.
    4. Yinghan Chen & Steven Andrew Culpepper & Yuguo Chen & Jeffrey Douglas, 2018. "Bayesian Estimation of the DINA Q matrix," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 89-108, March.
    5. Howard Wainer & Jee-Seon Kim & Terry Ackerman, 2001. "Reviews," Psychometrika, Springer;The Psychometric Society, vol. 66(2), pages 307-320, June.
    6. Anders Skrondal & Sophia Rabe‐Hesketh, 2007. "Latent Variable Modelling: A Survey," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(4), pages 712-745, December.

    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. 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.
    2. Robert Mislevy, 1986. "Bayes modal estimation in item response models," Psychometrika, Springer;The Psychometric Society, vol. 51(2), pages 177-195, June.
    3. Melissa Gladstone & Gillian Lancaster & Gareth McCray & Vanessa Cavallera & Claudia R. L. Alves & Limbika Maliwichi & Muneera A. Rasheed & Tarun Dua & Magdalena Janus & Patricia Kariger, 2021. "Validation of the Infant and Young Child Development (IYCD) Indicators in Three Countries: Brazil, Malawi and Pakistan," IJERPH, MDPI, vol. 18(11), pages 1-19, June.
    4. Herbert Hoijtink, 1990. "A latent trait model for dichotomous choice data," Psychometrika, Springer;The Psychometric Society, vol. 55(4), pages 641-656, December.
    5. Azevedo, Caio L.N. & Andrade, Dalton F. & Fox, Jean-Paul, 2012. "A Bayesian generalized multiple group IRT model with model-fit assessment tools," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4399-4412.
    6. J. Ramsay, 1989. "A comparison of three simple test theory models," Psychometrika, Springer;The Psychometric Society, vol. 54(3), pages 487-499, September.
    7. 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.
    8. Wendy Yen, 1987. "A comparison of the efficiency and accuracy of BILOG and LOGIST," Psychometrika, Springer;The Psychometric Society, vol. 52(2), pages 275-291, June.
    9. Azevedo, Caio L.N. & Bolfarine, Heleno & Andrade, Dalton F., 2011. "Bayesian inference for a skew-normal IRT model under the centred parameterization," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 353-365, January.
    10. Scott Monroe, 2021. "Testing Latent Variable Distribution Fit in IRT Using Posterior Residuals," Journal of Educational and Behavioral Statistics, , vol. 46(3), pages 374-398, June.
    11. Dean Follmann, 1988. "Consistent estimation in the rasch model based on nonparametric margins," Psychometrika, Springer;The Psychometric Society, vol. 53(4), pages 553-562, December.
    12. Haruhiko Ogasawara, 2009. "Asymptotic cumulants of the parameter estimators in item response theory," Computational Statistics, Springer, vol. 24(2), pages 313-331, May.
    13. Ping Chen & Chun Wang, 2021. "Using EM Algorithm for Finite Mixtures and Reformed Supplemented EM for MIRT Calibration," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 299-326, March.
    14. Javier Revuelta, 2010. "Estimating Difficulty from Polytomous Categorical Data," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 331-350, June.
    15. N. Verhelst & C. Glas, 1993. "A dynamic generalization of the Rasch model," Psychometrika, Springer;The Psychometric Society, vol. 58(3), pages 395-415, September.
    16. 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.
    17. Robert Mislevy, 1991. "Randomization-based inference about latent variables from complex samples," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 177-196, June.
    18. Sally Paganin & Christopher J. Paciorek & Claudia Wehrhahn & Abel Rodríguez & Sophia Rabe-Hesketh & Perry de Valpine, 2023. "Computational Strategies and Estimation Performance With Bayesian Semiparametric Item Response Theory Models," Journal of Educational and Behavioral Statistics, , vol. 48(2), pages 147-188, April.
    19. Sik-Yum Lee & Xin-Yuan Song, 2007. "A Unified Maximum Likelihood Approach for Analyzing Structural Equation Models With Missing Nonstandard Data," Sociological Methods & Research, , vol. 35(3), pages 352-381, February.
    20. Ying Cheng & Ke-Hai Yuan, 2010. "The Impact of Fallible Item Parameter Estimates on Latent Trait Recovery," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 280-291, June.

    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:61:y:1996:i:1:p:41-71. 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.