2011
DOI: 10.1080/00273171.2010.546733
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On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

Abstract: The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this multilevel framework. An advantage of the multilevel framework is that it allows relating person fit to explanatory variables for person misfit/fit. We critically discuss … Show more

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Cited by 7 publications
(5 citation statements)
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“…In a further alternative hybrid approach of design-based inference and model-based inference (see Ståhl et al, 2016), subjects can additionally be weighted by including weights ν P,n according to their fit to a statistical model. For example, model-based student-specific weights ν P,n can be derived according to their fit to the scaling model (person fit; see Conijn et al, 2011;Hong & Cheng, 2019;Raiche et al, 2012;Schuster & Yuan, 2011). In such an approach, students whose item responses are atypical with respect to the IRT model (e.g., non-scalable students; see Haertel, 1989) would be downweighted compared to students whose item responses are consistent with the IRT model.…”
Section: Model-assisted Design-based Inference For Personsmentioning
confidence: 99%
See 1 more Smart Citation
“…In a further alternative hybrid approach of design-based inference and model-based inference (see Ståhl et al, 2016), subjects can additionally be weighted by including weights ν P,n according to their fit to a statistical model. For example, model-based student-specific weights ν P,n can be derived according to their fit to the scaling model (person fit; see Conijn et al, 2011;Hong & Cheng, 2019;Raiche et al, 2012;Schuster & Yuan, 2011). In such an approach, students whose item responses are atypical with respect to the IRT model (e.g., non-scalable students; see Haertel, 1989) would be downweighted compared to students whose item responses are consistent with the IRT model.…”
Section: Model-assisted Design-based Inference For Personsmentioning
confidence: 99%
“…Moreover, the ability variable θ could also be redefined in a scaling model in which item responses and response times load on θ, resulting in a purified latent variable for speed (Costa et al, 2021). Furthermore, measurement models could also involve an additional student latent variable α n that characterizes person fit (Conijn et al, 2011;Ferrando, 2019;Raiche et al, 2012):…”
Section: The Role Of Test-taking Behavior In the Scaling Modelmentioning
confidence: 99%
“…Moreover, the ability variable θ could also be redefined in a scaling model in which item responses and response times load on θ, resulting in a purified latent variable for speed (Costa et al, 2021). Furthermore, measurement models could also involve an additional student latent variable α that characterizes person fit (Conijn et al, 2011;Ferrando, 2019;Raiche et al, 2012)…”
Section: The Role Of Test-taking Behavior In the Scaling Modelmentioning
confidence: 99%
“…Several tests of person fit are aimed at the detection of trait changes between subsets of items; see Klauer and Rettig (1990) and Glas and Dagohoy (2007) for example. The multilevel logistic regression approach of Reise (2000) also evaluates the constancy of θ over the test, but see Conijn, Emons, van Assen, and Sijtsma (2011) for a critical review of this approach.…”
Section: The Information Matrix Testmentioning
confidence: 99%