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Detecting Local Item Dependence in Polytomous Adaptive Data
Author(s) -
Mislevy Jessica L.,
Rupp André A.,
Harring Jeffrey R.
Publication year - 2012
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.2012.00165.x
Subject(s) - polytomous rasch model , item response theory , statistic , computerized adaptive testing , pairwise comparison , context (archaeology) , statistics , computer science , econometrics , psychology , psychometrics , mathematics , paleontology , biology
A rapidly expanding arena for item response theory (IRT) is in attitudinal and health‐outcomes survey applications, often with polytomous items. In particular, there is interest in computer adaptive testing (CAT). Meeting model assumptions is necessary to realize the benefits of IRT in this setting, however. Although initial investigations of local item dependence have been studied both for polytomous items in fixed‐form settings and for dichotomous items in CAT settings, there have been no publications applying local item dependence detection methodology to polytomous items in CAT despite its central importance to these applications. The current research uses a simulation study to investigate the extension of widely used pairwise statistics, Yen's Q 3 Statistic and Pearson's Statistic X 2 , in this context. The simulation design and results are contextualized throughout with a real item bank of this type from the Patient‐Reported Outcomes Measurement Information System (PROMIS).