IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v50y1985i1p69-82.html
   My bibliography  Save this article

A comparison of latent trait and latent class analyses of Likert-type data

Author

Listed:
  • Geofferey Masters

Abstract

No abstract is available for this item.

Suggested Citation

  • Geofferey Masters, 1985. "A comparison of latent trait and latent class analyses of Likert-type data," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 69-82, March.
    • Handle: RePEc:spr:psycho:v:50:y:1985:i:1:p:69-82
    DOI: 10.1007/BF02294149
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02294149
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02294149?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. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    2. R. Darrell Bock, 1972. "Estimating item parameters and latent ability when responses are scored in two or more nominal categories," Psychometrika, Springer;The Psychometric Society, vol. 37(1), pages 29-51, March.
    3. Geofferey Masters & Benjamin Wright, 1984. "The essential process in a family of measurement models," Psychometrika, Springer;The Psychometric Society, vol. 49(4), pages 529-544, December.
    4. Jürgen Rost, 1985. "A latent class model for rating data," Psychometrika, Springer;The Psychometric Society, vol. 50(1), pages 37-49, 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. 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.
    2. Xie, Jing Chao & Xue, Peng & Mak, Cheuk Ming & Liu, Jia Ping, 2017. "Balancing energy and daylighting performances for envelope design: A new index and proposition of a case study in Hong Kong," Applied Energy, Elsevier, vol. 205(C), pages 13-22.
    3. David Thissen & Lynne Steinberg, 1986. "A taxonomy of item response models," Psychometrika, Springer;The Psychometric Society, vol. 51(4), pages 567-577, December.
    4. 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.
    5. Jürgen Rost, 1988. "Rating scale analysis with latent class models," Psychometrika, Springer;The Psychometric Society, vol. 53(3), pages 327-348, September.
    6. Edward Haertel, 1990. "Continuous and discrete latent structure models for item response data," Psychometrika, Springer;The Psychometric Society, vol. 55(3), pages 477-494, 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. Gerhard Tutz & Moritz Berger, 2016. "Response Styles in Rating Scales," Journal of Educational and Behavioral Statistics, , vol. 41(3), pages 239-268, June.
    2. Albert Maydeu-Olivares & Harry Joe, 2006. "Limited Information Goodness-of-fit Testing in Multidimensional Contingency Tables," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 713-732, December.
    3. Yang Ann Shawing, 2015. "Measuring Self-Service Technology Latent Difficulties: Insurance Decisions on Utilitarian and Hedonic Influences," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 9(1), pages 1-33, January.
    4. David Andrich, 2010. "Sufficiency and Conditional Estimation of Person Parameters in the Polytomous Rasch Model," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 292-308, June.
    5. Gerhard Tutz, 2021. "Hierarchical Models for the Analysis of Likert Scales in Regression and Item Response Analysis," International Statistical Review, International Statistical Institute, vol. 89(1), pages 18-35, April.
    6. repec:jss:jstsof:35:i12 is not listed on IDEAS
    7. Maydeu Olivares, Alberto & D'Zurilla, Thomas J. & Morera, Osvaldo, 1996. "Assessing measurement invariance in questionnaires within latent trait models using item response theory," DES - Working Papers. Statistics and Econometrics. WS 10456, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Dylan Molenaar, 2015. "Heteroscedastic Latent Trait Models for Dichotomous Data," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 625-644, September.
    9. Bacci, Silvia & Fabbricatore, Rosa & Iannario, Maria, 2023. "Multilevel IRT models for the analysis of satisfaction for distance learning during the Covid-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    10. 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).
    11. Daphna Harel & Russell J. Steele, 2018. "An Information Matrix Test for the Collapsing of Categories Under the Partial Credit Model," Journal of Educational and Behavioral Statistics, , vol. 43(6), pages 721-750, December.
    12. 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.
    13. David Magis, 2015. "A Note on the Equivalence Between Observed and Expected Information Functions With Polytomous IRT Models," Journal of Educational and Behavioral Statistics, , vol. 40(1), pages 96-105, February.
    14. 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.
    15. Leonardo Grilli & Carla Rampichini, 2019. "Discussion of ‘The class of CUB models: statistical foundations, inferential issues and empirical evidence’ by Domenico Piccolo and Rosaria Simone," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 459-463, September.
    16. Michal Abrahamowicz & James Ramsay, 1992. "Multicategorical spline model for item response theory," Psychometrika, Springer;The Psychometric Society, vol. 57(1), pages 5-27, March.
    17. 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.
    18. David Magis, 2015. "A Note on Weighted Likelihood and Jeffreys Modal Estimation of Proficiency Levels in Polytomous Item Response Models," Psychometrika, Springer;The Psychometric Society, vol. 80(1), pages 200-204, March.
    19. Timothy R. Johnson & Daniel M. Bolt, 2010. "On the Use of Factor-Analytic Multinomial Logit Item Response Models to Account for Individual Differences in Response Style," Journal of Educational and Behavioral Statistics, , vol. 35(1), pages 92-114, February.
    20. Silvana Bortolotti & Rafael Tezza & Dalton Andrade & Antonio Bornia & Afonso Sousa Júnior, 2013. "Relevance and advantages of using the item response theory," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(4), pages 2341-2360, June.
    21. Javier Revuelta, 2008. "The generalized Logit-Linear Item Response Model for Binary-Designed Items," Psychometrika, Springer;The Psychometric Society, vol. 73(3), pages 385-405, September.

    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:50:y:1985:i:1:p:69-82. 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.