Item-focussed Trees for the Identification of Items in Differential Item Functioning
Gerhard Tutz () and
Moritz Berger
Additional contact information
Gerhard Tutz: Ludwig-Maximilians-Universität
Moritz Berger: Ludwig-Maximilians-Universität
Psychometrika, 2016, vol. 81, issue 3, No 7, 727-750
Abstract:
Abstract A novel method for the identification of differential item functioning (DIF) by means of recursive partitioning techniques is proposed. We assume an extension of the Rasch model that allows for DIF being induced by an arbitrary number of covariates for each item. Recursive partitioning on the item level results in one tree for each item and leads to simultaneous selection of items and variables that induce DIF. For each item, it is possible to detect groups of subjects with different item difficulties, defined by combinations of characteristics that are not pre-specified. The way a DIF item is determined by covariates is visualized in a small tree and therefore easily accessible. An algorithm is proposed that is based on permutation tests. Various simulation studies, including the comparison with traditional approaches to identify items with DIF, show the applicability and the competitive performance of the method. Two applications illustrate the usefulness and the advantages of the new method.
Keywords: Rasch model; differential item functioning; recursive partitioning; item-focussed trees (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1007/s11336-015-9488-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:psycho:v:81:y:2016:i:3:d:10.1007_s11336-015-9488-3
Ordering information: This journal article can be ordered from
http://www.springer. ... gy/journal/11336/PS2
DOI: 10.1007/s11336-015-9488-3
Access Statistics for this article
Psychometrika is currently edited by Irini Moustaki
More articles in Psychometrika from Springer, The Psychometric Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().