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Detection of regional Differential Item Functioning (DIF) utilizing a geographically weighted approach to Item Response Theory (IRT) (303424)

Mappings of spatially-varying Item Response Theory (IRT) parameters are proposed, allowing for visual investigation of potential Differential Item Functioning (DIF) based upon geographical location without need for pre-specified groupings. This proposed model merges Geographically Weighted Regression (GWR) and IRT methods, with the current emphasis being on a 1PL/Rasch model. This geographically weighted approach to IRT modeling and DIF detection provides a flexible framework, with various extensions discussed. Applications to simulated examination data, utilizing a kernel weighting scheme based on several fixed bandwidths as well as classically defined spatial neighborhood structures for both regular and irregular lattices, illustrates this method’s benefit and practical value when comparisons are made to traditional DIF techniques. This approach, making use of three-dimensional surface mappings of estimated item difficulty parameters, serves to detect DIF across space without a priori groupings, thereby identifying regional disparities in item functionality that may be unobservable on a global level.