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Adaptive Pairwise Comparison for Educational Measurement

Elise A. V. Crompvoets, Anton A. Béguin and Klaas Sijtsma
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Elise A. V. Crompvoets: Tilburg University
Anton A. Béguin: Cito
Klaas Sijtsma: Tilburg University

Journal of Educational and Behavioral Statistics, 2020, vol. 45, issue 3, 316-338

Abstract: Pairwise comparison is becoming increasingly popular as a holistic measurement method in education. Unfortunately, many comparisons are required for reliable measurement. To reduce the number of required comparisons, we developed an adaptive selection algorithm (ASA) that selects the most informative comparisons while taking the uncertainty of the object parameters into account. The results of the simulation study showed that, given the number of comparisons, the ASA resulted in smaller standard errors of object parameter estimates than a random selection algorithm that served as a benchmark. Rank order accuracy and reliability were similar for the two algorithms. Because the scale separation reliability (SSR) may overestimate the benchmark reliability when the ASA is used, caution is required when interpreting the SSR.

Keywords: adaptive measurement; comparative judgment; holistic measurement; pairwise comparison (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:45:y:2020:i:3:p:316-338

DOI: 10.3102/1076998619890589

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