caa a22 4500 606241787 CHVBK 20210128101315.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s11336-013-9377-6 doi (NATIONALLICENCE)springer-10.1007/s11336-013-9377-6 A Penalty Approach to Differential Item Functioning in Rasch Models [Elektronische Daten] [Gerhard Tutz, Gunther Schauberger] A new diagnostic tool for the identification of differential item functioning (DIF) is proposed. Classical approaches to DIF allow to consider only few subpopulations like ethnic groups when investigating if the solution of items depends on the membership to a subpopulation. We propose an explicit model for differential item functioning that includes a set of variables, containing metric as well as categorical components, as potential candidates for inducing DIF. The ability to include a set of covariates entails that the model contains a large number of parameters. Regularized estimators, in particular penalized maximum likelihood estimators, are used to solve the estimation problem and to identify the items that induce DIF. It is shown that the method is able to detect items with DIF. Simulations and two applications demonstrate the applicability of the method. The Psychometric Society, 2013 Rasch model nationallicence differential item functioning nationallicence penalized maximum likelihood nationallicence DIF lasso nationallicence Tutz Gerhard Department of Statistics, Ludwig-Maximilians-Universität, Munich, Germany aut Schauberger Gunther Department of Statistics, Ludwig-Maximilians-Universität, Munich, Germany aut Psychometrika Springer US; http://www.springer-ny.com 80/1(2015-03-01), 21-43 0033-3123 80:1<21 2015 80 11336 https://doi.org/10.1007/s11336-013-9377-6 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11336-013-9377-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Tutz Gerhard Department of Statistics, Ludwig-Maximilians-Universität, Munich, Germany aut NATIONALLICENCE 700 1- Schauberger Gunther Department of Statistics, Ludwig-Maximilians-Universität, Munich, Germany aut NATIONALLICENCE 773 0- Psychometrika Springer US; http://www.springer-ny.com 80/1(2015-03-01), 21-43 0033-3123 80:1<21 2015 80 11336