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Modeling item responses when different subjects employ different solution strategies


  • Robert Mislevy
  • Norman Verhelst


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Suggested Citation

  • Robert Mislevy & Norman Verhelst, 1990. "Modeling item responses when different subjects employ different solution strategies," Psychometrika, Springer;The Psychometric Society, vol. 55(2), pages 195-215, June.
  • Handle: RePEc:spr:psycho:v:55:y:1990:i:2:p:195-215
    DOI: 10.1007/BF02295283

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    References listed on IDEAS

    1. Robert Mislevy, 1986. "Bayes modal estimation in item response models," Psychometrika, Springer;The Psychometric Society, vol. 51(2), pages 177-195, June.
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    Cited by:

    1. Heike Heidemeier & Ursula Staudinger, 2012. "Self-Evaluation Processes in Life Satisfaction: Uncovering Measurement Non-Equivalence and Age-Related Differences," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 105(1), pages 39-61, January.
    2. Paul Westers & Henk Kelderman, 1992. "Examining differential item functioning due to item difficulty and alternative attractiveness," Psychometrika, Springer;The Psychometric Society, vol. 57(1), pages 107-118, March.
    3. Chun Wang & Gongjun Xu & Zhuoran Shang, 2018. "A Two-Stage Approach to Differentiating Normal and Aberrant Behavior in Computer Based Testing," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 223-254, March.
    4. Ulf Böckenholt & Ingo Böckenholt, 1991. "Constrained latent class analysis: Simultaneous classification and scaling of discrete choice data," Psychometrika, Springer;The Psychometric Society, vol. 56(4), pages 699-716, December.
    5. Dylan Molenaar, 2015. "Heteroscedastic Latent Trait Models for Dichotomous Data," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 625-644, September.
    6. Denny Borsboom, 2006. "The attack of the psychometricians," Psychometrika, Springer;The Psychometric Society, vol. 71(3), pages 425-440, September.
    7. Thomas Love, 1997. "Distractor selection ratios," Psychometrika, Springer;The Psychometric Society, vol. 62(1), pages 51-62, March.
    8. repec:spr:advdac:v:10:y:2016:i:1:p:53-70 is not listed on IDEAS
    9. Frank Rijmen & Paul De Boeck, 2005. "A relation between a between-item multidimensional IRT model and the mixture rasch model," Psychometrika, Springer;The Psychometric Society, vol. 70(3), pages 481-496, September.
    10. 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.
    11. 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.
    12. Carolin Strobl & Julia Kopf & Achim Zeileis, 2015. "Rasch Trees: A New Method for Detecting Differential Item Functioning in the Rasch Model," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 289-316, June.
    13. Steven Verheyen & Wouter Voorspoels & Gert Storms, 2015. "Inferring choice criteria with mixture IRT models: A demonstration using ad hoc and goal-derived categories," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(1), pages 97-114, January.
    14. Michela Gnaldi & Silvia Bacci & Francesco Bartolucci, 2016. "A multilevel finite mixture item response model to cluster examinees and schools," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(1), pages 53-70, March.


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