ArticleBehavior research methods2020
A regularization approach for the detection of differential item functioning in generalized partial credit models.
Article in Behavior research methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Estimating Trends With Differential Item Functioning: A Comparison of Five IRT-Based Approaches.Educational and psychological measurement · 2026Article
- Detecting Differential Item Functioning across Multiple Groups using Group Pairwise Penalty.Psychometrika · 2025Article
- Differential item functioning in neonatal behavioral neurological assessment in high-risk full-term infants in NICU based on a machine learning approach.Frontiers in neuroscience · 2025Article
- Personalized recommendation algorithm for rehabilitation intervention in children with autism spectrum disorder based on the cognitive diagnosis model.Frontiers in psychology · 2025Article
- Bayesian Adaptive Lasso for Detecting Item-Trait Relationship and Differential Item Functioning in Multidimensional Item Response Theory Models.Psychometrika · 2024Article
- DIF Analysis with Unknown Groups and Anchor Items.Psychometrika · 2024Article
- Article
- DIF Statistical Inference Without Knowing Anchoring Items.Psychometrika · 2023Article
- Semi-automated Rasch analysis with differential item functioning.Behavior research methods · 2023Article
- Identification of sources of DIF using covariates in patient-reported outcome measures: a simulation study comparing two approaches based on Rasch family models.Frontiers in psychology · 2023Article
- A Machine Learning Approach to Assess Differential Item Functioning of the KINDL Quality of Life Questionnaire Across Children with and Without ADHD.Child psychiatry and human development · 2022Article
- Differential item functioning of the Beck Anxiety Inventory in a rural, multi-ethnic cohort.Journal of affective disorders · 2021Article
- Differential Item Functioning Analysis Without A Priori Information on Anchor Items: QQ Plots and Graphical Test.Psychometrika · 2021Article
- Semi-automated Rasch analysis using in-plus-out-of-questionnaire log likelihood.The British journal of mathematical and statistical psychology · 2021Article
- Article
- A Machine Learning Approach to Assess Differential Item Functioning in Psychometric Questionnaires Using the Elastic Net Regularized Ordinal Logistic Regression in Small Sample Size Groups.BioMed research international · 2021Article
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2 authors.
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Abstract
Most common analysis tools for the detection of differential item functioning (DIF) in item response theory are restricted to the use of single covariates. If several variables have to be considered, the respective method is repeated independently for each variable. We propose a regularization approach based on the lasso principle for the detection of uniform DIF. It is applicable to a broad range of polytomous item response models with the generalized partial credit model as the most general case. A joint model is specified where the possible DIF effects for all items and all covariates are explicitly parameterized. The model is estimated using a penalized likelihood approach that automatically detects DIF effects and provides trait estimates that correct for the detected DIF effects from different covariates simultaneously. The approach is evaluated by means of several simulation studies. An application is presented using data from the children's depression inventory.
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