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ERIC Number: EJ921254
Record Type: Journal
Publication Date: 2011-Apr
Pages: 29
Abstractor: As Provided
Reference Count: 64
ISBN: N/A
ISSN: ISSN-0033-3123
Item Screening in Graphical Loglinear Rasch Models
Kreiner, Svend; Christensen, Karl Bang
Psychometrika, v76 n2 p228-256 Apr 2011
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.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A