Item Screening in Graphical Loglinear Rasch Models

Autor/inn/en	Kreiner, Svend; Christensen, Karl Bang
Titel	Item Screening in Graphical Loglinear Rasch Models
Quelle	In: Psychometrika, 76 (2011) 2, S.228-256 (29 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
DOI	10.1007/s11336-011-9203-y
Schlagwörter	Evidence; Markov Processes; Quality of Life; Item Analysis; Item Response Theory; Behavioral Sciences; Reliability; Models; Statistical Analysis; Test Bias; Data + Suchen Sie Ihr Suchwort? Evidenz; Markowscher Prozess; Lebensqualität; Itemanalyse; Item-Response-Theorie; Reliabilität; Analogiemodell; Statistische Analyse; Testkritik; Daten
Abstract	In behavioural sciences, local dependence and DIF are common, and purification procedures that eliminate items with these weaknesses often result in short scales with poor reliability. Graphical loglinear Rasch models (Kreiner & Christensen, in "Statistical Methods for Quality of Life Studies," ed. by M. Mesbah, F.C. Cole & M.T. Lee, Kluwer Academic, pp. 187-203, 2002) where uniform DIF and uniform local dependence are permitted solve this dilemma by modelling the local dependence and DIF. Identifying loglinear Rasch models by a stepwise model search is often very time consuming, since the initial item analysis may disclose a great deal of spurious and misleading evidence of DIF and local dependence that has to disposed of during the modelling procedure. Like graphical models, graphical loglinear Rasch models possess Markov properties that are useful during the statistical analysis if they are used methodically. This paper describes how. It contains a systematic study of the Markov properties and the way they can be used to distinguish spurious from genuine evidence of DIF and local dependence and proposes a strategy for initial item screening that will reduce the time needed to identify a graphical loglinear Rasch model that fits the item responses. The last part of the paper illustrates the item screening procedure on simulated data and on data on the PF subscale measuring physical functioning in the SF36 Health Survey inventory. (As Provided).
Anmerkungen	Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10