IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v81y2016i1p135-160.html
   My bibliography  Save this article

Item Response Models for Forced-Choice Questionnaires: A Common Framework

Author

Listed:
  • Anna Brown

Abstract

In forced-choice questionnaires, respondents have to make choices between two or more items presented at the same time. Several IRT models have been developed to link respondent choices to underlying psychological attributes, including the recent MUPP (Stark et al. in Appl Psychol Meas 29:184–203, 2005 ) and Thurstonian IRT (Brown and Maydeu-Olivares in Educ Psychol Meas 71:460–502, 2011 ) models. In the present article, a common framework is proposed that describes forced-choice models along three axes: (1) the forced-choice format used; (2) the measurement model for the relationships between items and psychological attributes they measure; and (3) the decision model for choice behavior. Using the framework, fundamental properties of forced-choice measurement of individual differences are considered. It is shown that the scale origin for the attributes is generally identified in questionnaires using either unidimensional or multidimensional comparisons. Both dominance and ideal point models can be used to provide accurate forced-choice measurement; and the rules governing accurate person score estimation with these models are remarkably similar. Copyright The Psychometric Society 2016

Suggested Citation

  • Anna Brown, 2016. "Item Response Models for Forced-Choice Questionnaires: A Common Framework," Psychometrika, Springer;The Psychometric Society, vol. 81(1), pages 135-160, March.
    • Handle: RePEc:spr:psycho:v:81:y:2016:i:1:p:135-160
    DOI: 10.1007/s11336-014-9434-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11336-014-9434-9
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11336-014-9434-9?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. Geert Soete & J. Carroll, 1983. "A maximum likelihood method for fitting the wandering vector model," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 553-566, December.
    2. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June.
    3. Daniel L. McFadden, 1976. "Quantal Choice Analysis: A Survey," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 363-390, National Bureau of Economic Research, Inc.
    4. Drasgow, Fritz & Chernyshenko, Oleksandr S. & Stark, Stephen, 2010. "75 Years After Likert: Thurstone Was Right!," Industrial and Organizational Psychology, Cambridge University Press, vol. 3(4), pages 465-476, December.
    5. Erling Andersen, 1976. "Paired comparisons with individual differences," Psychometrika, Springer;The Psychometric Society, vol. 41(2), pages 141-157, June.
    6. Yoshio Takane & Jan Leeuw, 1987. "On the relationship between item response theory and factor analysis of discretized variables," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 393-408, September.
    7. Joseph Zinnes & Richard Griggs, 1974. "Probabilistic, multidimensional unfolding analysis," Psychometrika, Springer;The Psychometric Society, vol. 39(3), pages 327-350, September.
    8. Joseph Bennett & William Hays, 1960. "Multidimensional unfolding: Determining the dimensionality of ranked preference data," Psychometrika, Springer;The Psychometric Society, vol. 25(1), pages 27-43, March.
    9. Brown, Anna & Maydeu-Olivares, Alberto, 2010. "Issues That Should Not Be Overlooked in the Dominance Versus Ideal Point Controversy," Industrial and Organizational Psychology, Cambridge University Press, vol. 3(4), pages 489-493, December.
    10. Albert Maydeu-Olivares, 1999. "Thurstonian modeling of ranking data via mean and covariance structure analysis," Psychometrika, Springer;The Psychometric Society, vol. 64(3), pages 325-340, September.
    11. Roger Shepard, 1957. "Stimulus and response generalization: A stochastic model relating generalization to distance in psychological space," Psychometrika, Springer;The Psychometric Society, vol. 22(4), pages 325-345, December.
    12. Henry Brady, 1989. "Factor and ideal point analysis for interpersonally incomparable data," Psychometrika, Springer;The Psychometric Society, vol. 54(2), pages 181-202, 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. Qian Wu & Monique Vanerum & Anouk Agten & Andrés Christiansen & Frank Vandenabeele & Jean-Michel Rigo & Rianne Janssen, 2021. "Certainty-Based Marking on Multiple-Choice Items: Psychometrics Meets Decision Theory," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 518-543, June.
    2. Susanne Frick, 2022. "Modeling Faking in the Multidimensional Forced-Choice Format: The Faking Mixture Model," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 773-794, June.
    3. Paul-Christian Bürkner, 2022. "On the Information Obtainable from Comparative Judgments," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1439-1472, December.
    4. Alwyn Lim & Shawn Pope, 2022. "What drives companies to do good? A “universal” ordering of corporate social responsibility motivations," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 29(1), pages 233-255, January.

    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. Maydeu-Olivares, Albert, 2002. "Limited information estimation and testing of Thurstonian models for preference data," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 467-483, July.
    2. Despoina Alempaki & Emina Canic & Timothy L. Mullett & William J. Skylark & Chris Starmer & Neil Stewart & Fabio Tufano, 2019. "Reexamining How Utility and Weighting Functions Get Their Shapes: A Quasi-Adversarial Collaboration Providing a New Interpretation," Management Science, INFORMS, vol. 65(10), pages 4841-4862, October.
    3. Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    4. Marley, A. A. J., 2002. "Random utility models and their applications: recent developments," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 289-302, July.
    5. Wayne DeSarbo & Kamel Jedidi & Joel Steckel, 1991. "A stochastic multidimensional scaling procedure for the empirical determination of convex indifference curves for preference/choice analysis," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 279-307, June.
    6. Filip Matêjka & Alisdair McKay, 2015. "Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model," American Economic Review, American Economic Association, vol. 105(1), pages 272-298, January.
    7. Robert Kapłon, 2006. "A retrospective review of categorical data analysis – theory and marketing practice," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 16(1), pages 55-72.
    8. Anders Skrondal & Sophia Rabe-Hesketh, 2003. "Multilevel logistic regression for polytomous data and rankings," Psychometrika, Springer;The Psychometric Society, vol. 68(2), pages 267-287, June.
    9. Ulf Böckenholt, 1990. "Multivariate thurstonian models," Psychometrika, Springer;The Psychometric Society, vol. 55(2), pages 391-403, June.
    10. Duffy, Sean & Gussman, Steven & Smith, John, 2019. "Judgments of length in the economics laboratory: Are there brains in choice?," MPRA Paper 93126, University Library of Munich, Germany.
    11. Duffy, Sean & Smith, John, 2020. "An economist and a psychologist form a line: What can imperfect perception of length tell us about stochastic choice?," MPRA Paper 99417, University Library of Munich, Germany.
    12. Duffy, Sean & Gussman, Steven & Smith, John, 2021. "Visual judgments of length in the economics laboratory: Are there brains in stochastic choice?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 93(C).
    13. DeSarbo Wayne S., 2010. "A Spatial Multidimensional Unfolding Choice Model for Examining the Heterogeneous Expressions of Sports Fan Avidity," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 6(2), pages 1-24, April.
    14. Breitmoser, Yves, 2018. "The Axiomatic Foundation of Logit," Rationality and Competition Discussion Paper Series 78, CRC TRR 190 Rationality and Competition.
    15. Albert Maydeu-Olivares, 2001. "Limited information estimation and testing of Thurstonian models for paired comparison data under multiple judgment sampling," Psychometrika, Springer;The Psychometric Society, vol. 66(2), pages 209-227, June.
    16. JIMENEZ Edward, 2002. "Unified Game Theory," Computing in Economics and Finance 2002 25, Society for Computational Economics.
    17. Roger Shepard, 1974. "Representation of structure in similarity data: Problems and prospects," Psychometrika, Springer;The Psychometric Society, vol. 39(4), pages 373-421, December.
    18. Czajkowski, Mikołaj & Zagórska, Katarzyna & Letki, Natalia & Tryjanowski, Piotr & Wąs, Adam, 2021. "Drivers of farmers’ willingness to adopt extensive farming practices in a globally important bird area," Land Use Policy, Elsevier, vol. 107(C).
    19. Weck-Hannemann, Hannelore, 1989. "Protectionism in direct democracy," Discussion Papers, Series II 79, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
    20. Ichimura, Hidehiko & Thompson, T. Scott, 1998. "Maximum likelihood estimation of a binary choice model with random coefficients of unknown distribution," Journal of Econometrics, Elsevier, vol. 86(2), pages 269-295, 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:81:y:2016:i:1:p:135-160. 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.