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The Specification of Attribute Structures and Its Effects on Classification Accuracy in Diagnostic Test Design

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Quantitative Psychology Research

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 167))

Abstract

Diagnostic test has gained attention for its potentiality to produce fine-grained information about examinees. The dependency among attributes (i.e. attribute structure) is one of the most important factors affecting diagnostic test design. This article introduces four types of attribute structures and examines the effects of the attribute number, structure and level on classification accuracy and reliability. Results from the study help researchers and practitioners understand factors that affect classification when specifying attributes, and design diagnostic tests that provide accurate information about examinees.

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Author information

Authors and Affiliations

  1. Department of Research and Evaluation Methodology, University of Florida, Gainesville, FL, 32611, USA

    Ren Liu & Anne Corinne Huggins-Manley

Authors
  1. Ren Liu
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  2. Anne Corinne Huggins-Manley
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Corresponding author

Correspondence to Ren Liu .

Editor information

Editors and Affiliations

  1. University of Amsterdam, Amsterdam, The Netherlands

    L. Andries van der Ark

  2. University of Wisconsin, Madison, Wisconsin, USA

    Daniel M. Bolt

  3. Education University of Hong Kong, Hong Kong, China

    Wen-Chung Wang

  4. University of Illinois, Champaign, Illinois, USA

    Jeffrey A. Douglas

  5. Umeå University, Umeå, Sweden

    Marie Wiberg

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Liu, R., Huggins-Manley, A.C. (2016). The Specification of Attribute Structures and Its Effects on Classification Accuracy in Diagnostic Test Design. In: van der Ark, L., Bolt, D., Wang, WC., Douglas, J., Wiberg, M. (eds) Quantitative Psychology Research. Springer Proceedings in Mathematics & Statistics, vol 167. Springer, Cham. https://doi.org/10.1007/978-3-319-38759-8_18

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