[en] This talk focuses on the issue of differential item functioning in psychometrics. An item is said to function differently if examinees from different groups, but with the same ability levels, have nevertheless different probabilities of endorsing this item. Many methods were proposed to detect DIF, either based on statistical methods (such as logistic regression) or on IRT models.
The talk is divided into three parts. In the first part, a brief overview of the DIF framework and methods is proposed. In the second part, a recent, conceptually different approach to DIF will be introduced. It consists basically in flagging as DIF, the items that are outlying withb respect to other items. This approach is based on robust statistical tools for outlier identification. It cancels the issue of Type I error inflation and the need for purification of the anchor set. In the third part, it is briefly outlined how this approach easily extends to the simultaneous comparison of more than two groups of examinees; multivariate robust estimators of location and scale are required, but their use might overcome the standard methods for simultaneous pairwise comparisons.
Disciplines :
Mathematics
Author, co-author :
Magis, David ; Université de Liège - ULiège > Département de mathématique > Statistique mathématique
Language :
English
Title :
Robust DIF analysis
Alternative titles :
[en] Analsyse robuste du fonctionnement différentiel d'items
Publication date :
11 October 2011
Event name :
MTO colloquium
Event organizer :
Department Methodology and Statistics, Tilburg University