Computerized Adaptive Testing with the Zinnes and Griggs Pairwise Preference Ideal Point Model
CAT, ideal point, IRT, paired comparison, performance assessment
Digital Object Identifier (DOI)
This article delves into a relatively unexplored area of measurement by focusing on adaptive testing with unidimensional pairwise preference items. The use of such tests is becoming more common in applied non-cognitive assessment because research suggests that this format may help to reduce certain types of rater error and response sets commonly associated with the traditional single stimulus format. Yet there have been no publications evaluating the performance of unidimensional pairwise preference adaptive or nonadaptive tests. This article therefore presents the results of a simulation study that examined scoring accuracy for three item selection algorithms (nonadaptive, adaptive-symmetric, and adaptive-asymmetric), two pool sizes (50 and 100 stimuli), two methods for pool composition (even- and over-sampling), and three test lengths (10, 20, and 40 items).
Was this content written or created while at USF?
Citation / Publisher Attribution
International Journal of Testing, v. 11, issue 3, p. 231-247
Scholar Commons Citation
Stark, Stephen and Chernyshenko, Oleksandr S., "Computerized Adaptive Testing with the Zinnes and Griggs Pairwise Preference Ideal Point Model" (2011). Psychology Faculty Publications. 1950.