A Mixture Model Analysis of Differential Item Functioning
By Allan S. Cohen, D. Bolt. 2005
214 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Experimental and Cognitive Psychology, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/da06f6cd16677adb9e1aae1877876985711252c6
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In Computer Networks and Communications
In Experimental and Cognitive Psychology
In Management Science and Operations Research
Citations in the corpus
- The Role of Extended Time and Item Content on a High–Stakes Mathematics Test (2005, methodology): “In a mixture DIF model, the researcher first defines the dimension according to which DIF occurs, and then looks at examinee or test characteristics associated with thatdimensioninanattempttounderstandthecause(s)ofDIF (Cohen&Bolt,2005).”
- Item response theory and clinical measurement. (2009, background): “Cohen & Bolt (2005), endorse this idea and argue that researchers are looking for qualitative differences in trait manifestations (i.e., DIF) in the wrong places.”
- A Multilevel Mixture IRT Model With an Application to DIF (2010, methodology): “Unfortunately, comparisons among members of manifest groups cannot accurately identify those examinees in each group who do or do not respond differentially to an item (Cohen & Bolt, 2005; Cohen et al., 2005; DeAyala, Kim, Stapleton, & Dayton, 2002; Samuelsen, 2005).”
- A Synthesis of 15 Years of Research on DIF in Language Testing: Methodological Advances, Challenges, and Recommendations (2007, methodology): “Taking a confirmatory statistical approach, Cohen and Bolt (2002) successfully applied a two-group mixture model to explain the causes of DIF for male and female learners, who had been found to differ on a college-level English placement test in a previous study.”
- Model Selection Methods for Mixture Dichotomous IRT Models (2009, methodology): “Mixture IRT models have also been used for detecting differential functioning of items (Cohen & Bolt, 2005; Cohen, Gregg, & Deng, 2005; Samuelsen, 2008) and testlets (Cohen, Cho, & Kim, 2005).”
- Fitting a Mixture Item Response Theory Model to Personality Questionnaire Data: Characterizing Latent Classes and Investigating Possibilities for Improving Prediction (2008, background): “Cohen and Bolt (2005) showed that manifest characteristics associated with DIF are not necessarily identical to the characteristics of the latent classes for which an item may be biased. Often, mixture IRT models focus on differences across latent classes in the use of the response scale that applie”