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Rejoinder to Commentaries on Lyu, Bolt and Westby’s “Exploring the Effects of Item Specific Factors in Sequential and IRTree Models”

Published online by Cambridge University Press:  01 January 2025

Weicong Lyu Open the ORCID record for Weicong Lyu [Opens in a new window]  and
Daniel M. Bolt
Weicong Lyu*
Affiliation:
University of Wisconsin-Madison
Daniel M. Bolt
Affiliation:
University of Wisconsin-Madison
*
Correspondence should be made to Weicong Lyu, University of Wisconsin-Madison, 880 Educational Sciences, 1025 West Johnson Street, Madison, WI 53706, USA. Email: wlyu4@wisc.edu
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Abstract

We respond to the commentaries on Lyu, Bolt and Westby’s “Exploring the effects of item specific factors in sequential and IRTree models.” The commentaries raise important points that allow us to clarify our theoretical expectation for item specific factors in many educational and psychological test items. At the same time, we agree with the commentaries in acknowledging challenges associated with providing empirical evidence for their presence and reflect on strategies that might support their estimation. We maintain that the principal concern is the ambiguity item specific factors create in attempting to interpret or use the parameters beyond the first node.

Keywords

sequential IRT modelsIRTree modelsspecific factors

Information

Type
Theory & Methods
Information
Psychometrika , Volume 88 , Issue 3 , September 2023 , pp. 1026 - 1031
Copyright
Copyright © 2023 The Author(s) under exclusive licence to The Psychometric Society

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References

Culpepper, S. A.(2014).If at first you don’t succeed, try, try again: Applications of sequential IRT models to cognitive assessments.Applied Psychological Measurement,38(8),632–644.CrossRefGoogle Scholar
DeBoeck, P. (2023, in press) Item specific factors in IRTree models: When they matter and when they don’t [Commentary on Lyu, W., Bolt, D.M., & Westby, S. (2023)]. Psychometrika.Google Scholar
Jeon, M. (2023). Explore conditional dependencies in item response tree data [Commentary on Lyu, W., Bolt, D.M., Westby, S. (2023)]. Psychometrika. https://10.1007/s11336-023-09915-8.CrossRefGoogle Scholar
Jeon, M., De Boeck, P., &van der Linden, W.(2017).Modeling answer change behavior: An application of a generalized item response tree model.Journal of Educational and Behavioral Statistics,42(4),467–490.CrossRefGoogle Scholar
Lyu, W., Bolt, D.M., & Westby, S. (2023). Exploring the effects of item specific factors in sequential and IRTree models. Psychometrika. https://10.1007/s11336-023-09912-x.CrossRefGoogle Scholar
Magnus, B. E., &Liu, Y.(2022).Symptom presence and symptom severity as unique indicators of psychopathology: An application of multidimensional zero-inflated and hurdle graded response models.Educational and Psychological Measurement,82(5),938–966.CrossRefGoogle ScholarPubMed
Magnus, B. E., &Garnier-Villarreal, M.(2022).A multidimensional zero-inflated graded response model for ordinal symptom data.Psychological Methods,27(2),261–279.CrossRefGoogle ScholarPubMed
Spray, J.A. (1997). Multiple-attempt, single-item response models. In W.J. van der Linden & R. K. Hambleton (Eds.) Handbook of modern item response theory (pp. 209-220). Springer. https://10.1007/978-1-4757-2691-6_12.CrossRefGoogle Scholar