Quantifying Local, Response Dependence between Two Polytomous Items Using the Rasch Model

Autor/inn/en	Andrich, David; Humphry, Stephen M.; Marais, Ida
Titel	Quantifying Local, Response Dependence between Two Polytomous Items Using the Rasch Model
Quelle	In: Applied Psychological Measurement, 36 (2012) 4, S.309-324 (16 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621612441858
Schlagwörter	Test Theory; Models; Item Response Theory; Evidence; Correlation; Test Construction; Goodness of Fit; Computation + Suchen Sie Ihr Suchwort? Testtheorie; Analogiemodell; Item-Response-Theorie; Evidenz; Korrelation; Testaufbau
Abstract	Models of modern test theory imply statistical independence among responses, generally referred to as "local independence." One violation of local independence occurs when the response to one item governs the response to a subsequent item. Expanding on a formulation of this kind of violation as a process in the dichotomous Rasch model, this article generalizes the dependence process to the case of the unidimensional, polytomous Rasch model. It then shows how the magnitude of this violation can be estimated as a change in the location of thresholds separating adjacent categories in the second item caused by the response dependence on the first. As in the dichotomous model, it is suggested that this index is relatively more tangible in interpretation than other indices of dependence that are either a weight in the interaction term in a model or a correlation coefficient. One function of this method of assessing dependence is likely to be in the development of tests and assessment formats where evidence of the magnitude of dependence of one item on another in a pilot study can be used as part of the evidence in deciding which items will be retained in a final version of a test or which formats might need to be reconstructed. A second function might be to identify the magnitude of response dependence that may then need to be taken into account in some other way, perhaps by applying a model that takes account of the dependence. (Contains 1 figure and 6 tables.) (As Provided).
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Update	2017/4/10