IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v76y2011i2p318-336.html
   My bibliography  Save this article

Measuring Growth in a Longitudinal Large-Scale Assessment with a General Latent Variable Model

Author

Listed:
  • Matthias Davier
  • Xueli Xu
  • Claus Carstensen

Abstract

No abstract is available for this item.

Suggested Citation

  • Matthias Davier & Xueli Xu & Claus Carstensen, 2011. "Measuring Growth in a Longitudinal Large-Scale Assessment with a General Latent Variable Model," Psychometrika, Springer;The Psychometric Society, vol. 76(2), pages 318-336, April.
    • Handle: RePEc:spr:psycho:v:76:y:2011:i:2:p:318-336
    DOI: 10.1007/s11336-011-9202-z
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11336-011-9202-z
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11336-011-9202-z?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. Erling Andersen, 1985. "Estimating latent correlations between repeated testings," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 3-16, March.
    2. Li Cai, 2010. "High-dimensional Exploratory Item Factor Analysis by A Metropolis–Hastings Robbins–Monro Algorithm," Psychometrika, Springer;The Psychometric Society, vol. 75(1), pages 33-57, March.
    3. Robert Mislevy, 1991. "Randomization-based inference about latent variables from complex samples," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 177-196, June.
    4. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    5. Gerhard Fischer, 1995. "Some neglected problems in IRT," Psychometrika, Springer;The Psychometric Society, vol. 60(4), pages 459-487, December.
    6. 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.
    7. Andrade, Dalton F. & Tavares, Heliton R., 2005. "Item response theory for longitudinal data: population parameter estimation," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 1-22, July.
    8. Susan Embretson, 1991. "A multidimensional latent trait model for measuring learning and change," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 495-515, September.
    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. Sun-Joo Cho & Allan Cohen & Brian Bottge, 2013. "Detecting Intervention Effects Using a Multilevel Latent Transition Analysis with a Mixture IRT Model," Psychometrika, Springer;The Psychometric Society, vol. 78(3), pages 576-600, July.
    2. Chun Wang & Steven W. Nydick, 2020. "On Longitudinal Item Response Theory Models: A Didactic," Journal of Educational and Behavioral Statistics, , vol. 45(3), pages 339-368, June.
    3. Matthias von Davier & Lale Khorramdel & Qiwei He & Hyo Jeong Shin & Haiwen Chen, 2019. "Developments in Psychometric Population Models for Technology-Based Large-Scale Assessments: An Overview of Challenges and Opportunities," Journal of Educational and Behavioral Statistics, , vol. 44(6), pages 671-705, December.
    4. Wallin, Gabriel & Chen, Yunxiao & Moustaki, Irini, 2024. "DIF analysis with unknown groups and anchor items," LSE Research Online Documents on Economics 121991, London School of Economics and Political Science, LSE Library.
    5. Peida Zhan & Hong Jiao & Dandan Liao & Feiming Li, 2019. "A Longitudinal Higher-Order Diagnostic Classification Model," Journal of Educational and Behavioral Statistics, , vol. 44(3), pages 251-281, June.

    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. Peida Zhan & Hong Jiao & Dandan Liao & Feiming Li, 2019. "A Longitudinal Higher-Order Diagnostic Classification Model," Journal of Educational and Behavioral Statistics, , vol. 44(3), pages 251-281, June.
    2. Chun Wang & Steven W. Nydick, 2020. "On Longitudinal Item Response Theory Models: A Didactic," Journal of Educational and Behavioral Statistics, , vol. 45(3), pages 339-368, June.
    3. Li Cai & Carrie R. Houts, 2021. "Longitudinal Analysis of Patient-Reported Outcomes in Clinical Trials: Applications of Multilevel and Multidimensional Item Response Theory," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 754-777, September.
    4. Sun-Joo Cho & Allan Cohen & Brian Bottge, 2013. "Detecting Intervention Effects Using a Multilevel Latent Transition Analysis with a Mixture IRT Model," Psychometrika, Springer;The Psychometric Society, vol. 78(3), pages 576-600, July.
    5. Shiyu Wang & Yan Yang & Steven Andrew Culpepper & Jeffrey A. Douglas, 2018. "Tracking Skill Acquisition With Cognitive Diagnosis Models: A Higher-Order, Hidden Markov Model With Covariates," Journal of Educational and Behavioral Statistics, , vol. 43(1), pages 57-87, February.
    6. Georg Gittler & Gerhard Fischer, 2011. "IRT-Based Measurement of Short-Term Changes of Ability, With an Application to Assessing the “Mozart Effectâ€," Journal of Educational and Behavioral Statistics, , vol. 36(1), pages 33-75, February.
    7. Stefano Noventa & Luca Stefanutti & Giulio Vidotto, 2014. "An Analysis of Item Response Theory and Rasch Models Based on the Most Probable Distribution Method," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 377-402, July.
    8. Matthew J. Madison & Laine P. Bradshaw, 2018. "Assessing Growth in a Diagnostic Classification Model Framework," Psychometrika, Springer;The Psychometric Society, vol. 83(4), pages 963-990, December.
    9. De Boeck, Paul & Partchev, Ivailo, 2012. "IRTrees: Tree-Based Item Response Models of the GLMM Family," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(c01).
    10. Singh, Jagdip, 2004. "Tackling measurement problems with Item Response Theory: Principles, characteristics, and assessment, with an illustrative example," Journal of Business Research, Elsevier, vol. 57(2), pages 184-208, February.
    11. Minjeong Jeon & Sophia Rabe-Hesketh, 2016. "An autoregressive growth model for longitudinal item analysis," Psychometrika, Springer;The Psychometric Society, vol. 81(3), pages 830-850, September.
    12. Chengyu Cui & Chun Wang & Gongjun Xu, 2024. "Variational Estimation for Multidimensional Generalized Partial Credit Model," Psychometrika, Springer;The Psychometric Society, vol. 89(3), pages 929-957, September.
    13. Olsbjerg, Maja & Christensen, Karl Bang, 2015. "%lrasch_mml: A SAS Macro for Marginal Maximum Likelihood Estimation in Longitudinal Polytomous Rasch Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(c02).
    14. César Merino-Soto & Gina Chávez-Ventura & Verónica López-Fernández & Guillermo M. Chans & Filiberto Toledano-Toledano, 2022. "Learning Self-Regulation Questionnaire (SRQ-L): Psychometric and Measurement Invariance Evidence in Peruvian Undergraduate Students," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    15. Padilla, Juan L. & Azevedo, Caio L.N. & Lachos, Victor H., 2018. "Multidimensional multiple group IRT models with skew normal latent trait distributions," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 250-268.
    16. Anja C. Rohenkohl & Monika Bullinger & Andreas M. Pleil & Levente Kriston & Julia H. Quitmann, 2016. "A Brief Version of the Quality of Life in Short Stature Youth Questionnaire - the QoLISSY-Brief," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 9(4), pages 971-984, December.
    17. Roberto Burro & Riccardo Sartori & Giulio Vidotto, 2011. "The method of constant stimuli with three rating categories and the use of Rasch models," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(1), pages 43-58, January.
    18. P. A. Ferrari & S. Salini, 2008. "Measuring Service Quality: The Opinion of Europeans about Utilities," Working Papers 2008.36, Fondazione Eni Enrico Mattei.
    19. Chang, Hsin-Li & Yang, Cheng-Hua, 2008. "Explore airlines’ brand niches through measuring passengers’ repurchase motivation—an application of Rasch measurement," Journal of Air Transport Management, Elsevier, vol. 14(3), pages 105-112.
    20. Merkle, Edgar C. & Steyvers, Mark & Mellers, Barbara & Tetlock, Philip E., 2017. "A neglected dimension of good forecasting judgment: The questions we choose also matter," International Journal of Forecasting, Elsevier, vol. 33(4), pages 817-832.

    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:76:y:2011:i:2:p:318-336. 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.