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Differential item functioning (DIF) arises alongside latent population heterogeneity in many applications, and both must be accounted for when assessing measurement invariance. In many practical settings, however, the comparison groups are…

Methodology · Statistics 2026-05-08 Gabriel Wallin , Qi Huang

This paper proposes a method for assessing differential item functioning (DIF) in item response theory (IRT) models. The method does not require pre-specification of anchor items, which is its main virtue. It is developed in two main steps,…

Methodology · Statistics 2025-01-08 Peter F. Halpin

Testing fairness is a major concern in psychometric and educational research. A typical approach for ensuring testing fairness is through differential item functioning (DIF) analysis. DIF arises when a test item functions differently across…

Applications · Statistics 2025-04-02 Ling Chen , Susu Zhang , Jingchen Liu

Item response theory (IRT) models typically rely on a normality assumption for subject-specific latent traits, which is often unrealistic in practice. Semiparametric extensions based on Dirichlet process mixtures offer a more flexible…

Within the educational context, students' assessment tests are routinely validated through Item Response Theory (IRT) models which assume unidimensionality and absence of Differential Item Functioning (DIF). In this paper, we investigate if…

Applications · Statistics 2012-12-04 Michela Gnaldi , Francesco Bartolucci , Silvia Bacci

Measurement non-invariance arises when the psychometric properties of a scale differ across subgroups, undermining the validity of group comparisons. At the item level, such non-invariance manifests as differential item functioning (DIF),…

Methodology · Statistics 2026-01-27 Gabriel Wallin , Qi Huang

In the item response theory (IRT) literature, differential test functioning (DTF) has been conceptualized in terms of how the test response function differs over groups of respondents. This paper presents an alternative approach to DTF that…

Methodology · Statistics 2026-02-10 Peter F. Halpin

Item Response Theory (IRT) models are widely used to estimate respondents' latent abilities and calibrate item difficulty. Traditional IRT estimation typically requires centralizing all raw responses, raising privacy and governance…

Machine Learning · Computer Science 2026-04-07 Biying Zhou , Nanyu Luo , Feng Ji

Ensuring fairness in instruments like survey questionnaires or educational tests is crucial. One way to address this is by a Differential Item Functioning (DIF) analysis, which examines if different subgroups respond differently to a…

Methodology · Statistics 2025-01-08 Gabriel Wallin , Yunxiao Chen , Irini Moustaki

Differential item functioning (DIF) is a widely used statistical notion for identifying items that may disadvantage specific groups of test-takers. These groups are often defined by non-manipulable characteristics, e.g., gender,…

Methodology · Statistics 2026-01-21 Youmi Suk , Weicong Lyu

A new method for the identification of differential item functioning (DIF) by using recursive partitioning techniques is proposed. We assume an extension of the Rasch model that allows for DIF being induced by an arbitrary number of…

Methodology · Statistics 2015-02-17 Gerhard Tutz , Moritz Berger

Establishing the invariance property of an instrument is a key step for establishing its measurement validity. Measurement invariance is typically assessed by differential item functioning (DIF) analysis, i.e., detecting DIF items whose…

Methodology · Statistics 2025-01-08 Yunxiao Chen , Chengcheng Li , Jing Ouyang , Gongjun Xu

Item Response Theory (IRT) is a ubiquitous model for understanding human behaviors and attitudes based on their responses to questions. Large modern datasets offer opportunities to capture more nuances in human behavior, potentially…

Machine Learning · Computer Science 2022-07-29 Mike Wu , Richard L. Davis , Benjamin W. Domingue , Chris Piech , Noah Goodman

Various methods to detect differential item functioning (DIF) in item response models are available. However, most of the methods assume that the responses are binary, for ordered response categories available methods are scarce. In the…

Methodology · Statistics 2016-09-29 Stella Bollmann , Moritz Berger , Gerhard Tutz

Cognitive diagnosis is a fundamental and crucial task in many educational applications, e.g., computer adaptive test and cognitive assignments. Item Response Theory (IRT) is a classical cognitive diagnosis method which can provide…

Artificial Intelligence · Computer Science 2019-12-03 Song Cheng , Qi Liu

Differential item functioning (DIF) detection is an important yet understudied problem in computerized adaptive testing (CAT). In this article, we proposed a two-level logistic model to improve DIF detection in CAT by explicitly accounting…

Applications · Statistics 2026-05-05 Dandan Chen Kaptur , Justin Kern , Chingwei David Shin , Jinming Zhang

Item Response Theory (IRT) is a ubiquitous model for understanding humans based on their responses to questions, used in fields as diverse as education, medicine and psychology. Large modern datasets offer opportunities to capture more…

Machine Learning · Computer Science 2020-03-17 Mike Wu , Richard L. Davis , Benjamin W. Domingue , Chris Piech , Noah Goodman

Item response theory (IRT) has become one of the most popular statistical models for psychometrics, a field of study concerned with the theory and techniques of psychological measurement. The IRT models are latent factor models tailored to…

Methodology · Statistics 2021-08-20 Yunxiao Chen , Xiaoou Li , Jingchen Liu , Zhiliang Ying

Detection of differential item functioning by use of the logistic modelling approach has a long tradition. One big advantage of the approach is that it can be used to investigate non-uniform DIF as well as uniform DIF. The classical…

Methodology · Statistics 2015-11-24 Moritz Berger , Gerhard Tutz

This study introduces a novel nonparametric approach for detecting Differential Item Functioning (DIF) in binary items through direct comparison of Item Response Curves (IRCs). Building on prior work on nonparametric comparison of…

Methodology · Statistics 2025-11-25 Adéla Hladká , Patrícia Martinková
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