Quotation Salzberger, Thomas, Horton, Mike. 2018. Does the threshold distribution in polytomous items matter in computer adaptive testing? IOMW (International Objective Measurement Workshop/Conference), New York, United States/USA, 10.04.-12.04.


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Abstract

Computer adaptive testing (CAT) contributes to efficiency in measurement by administering the smallest possible number of items while obtaining a predefined level of the standard error of measurement. Since polytomous items provide more information than dichotomous items, they are also suitable for CAT. Information depends on the distribution of thresholds raising the question whether more broadly or more narrowly distributed thresholds are preferable. A series of simulations using CAT software revealed that narrowly distributed thresholds contribute more to measurement precision even at an early stage of CAT provided the items cover a broad range of the continuum and proper targeting is ensured. While broadly distributed thresholds may compensate for small variation in the items’ overall locations, we argue that in the interest of validity and interpretation more variation in the items is desirable and fine graded, but distinguishable, categories appear to be the best option for CAT and fixed scales.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Paper presented at an academic conference or symposium
Language English
Title Does the threshold distribution in polytomous items matter in computer adaptive testing?
Event IOMW (International Objective Measurement Workshop/Conference)
Year 2018
Date 10.04.-12.04.
Country United States/USA
Location New York

Associations

People
Salzberger, Thomas (Details)
External
Horton, Mike (University of Leeds, United Kingdom)
Organization
Institute for Statistics and Mathematics IN (Details)
Research areas (ÖSTAT Classification 'Statistik Austria')
3925 Health sciences (Details)
5307 Business and management economics (Details)
5320 Marketing (Details)
5321 Market research (Details)
5912 Social sciences (interdisciplinary) (Details)
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