title: Exploring the Utility of Logistic Mixed Modeling Approaches to Simultaneously Investigate Item and Testlet DIF on Testlet-based Data.
abstract: This study explored the utility of logistic mixed models for the analysis of differential item functioning when item response data were testlet-based. Decomposition of differential item functioning (DIF) into item level and testlet level for the testlet-based data was introduced to separate possible sources of DIF: (1) an item, (2) a testlet, and (3) both the item and the testlet. Simulation study was conducted to investigate the performance of several logistic mixed models as well as the Mantel-Haenszel method under the conditions, in which the item-related DIF and testlet-related DIF were present simultaneously. The results revealed that a new DIF model based on a logistic mixed model with random item effects and item covariates could capture the item-related DIF and testlet-related DIF well under certain conditions.
authors.affiliation: Hirotaka Fukuhara, Pearson, 19500 Bulverde Road, San Antonio, TX 78259, USA, Hiro.Fukuhara@Pearson.com.
authors.forename: Hirotaka
authors.initials: H
authors.lastname: Fukuhara
authors.forename: Insu
authors.initials: I
authors.lastname: Paek
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004521:Educational Measurement / Q000379:methods*; D015233:Models, Statistical; D011594:Psychometrics / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D011795:Surveys and Questionnaires