Journal article
Observed score reliability indices in diagnostic classification models
Behaviormetrika, Vol.49(1), pp.47-68
2022
DOI: 10.1007/s41237-021-00153-9
Abstract
Quantifying the reliability of latent variable estimates in diagnostic classification models has been a difficult topic, complicated by the classification-based nature of these models. In this study, we derive observed score reliability indices based on diagnostic classification models as an extension of classical test theory-based reliability. Additionally, we derive conditional observed sum- and sub-score distributions. In this manner, various conditional expectations and conditional standard error of measurement estimates can be calculated for both sum- and sub-scores of a test. The proposed methods provide a variety of expectations and standard errors for attribute estimates, which we demonstrate with an analysis of an empirical test. Moreover, a simulation study revealed the proposed sub-score-based reliability index was correlated to a previously developed attribute mastery reliability index.
Details
- Title: Subtitle
- Observed score reliability indices in diagnostic classification models
- Creators
- Kazuhiro Yamaguchi - University of TsukubaJonathan Templin - The University of Iowa
- Resource Type
- Journal article
- Publication Details
- Behaviormetrika, Vol.49(1), pp.47-68
- Publisher
- Springer Japan
- DOI
- 10.1007/s41237-021-00153-9
- ISSN
- 0385-7417
- eISSN
- 1349-6964
- Grant note
- JSPS Grant-in-Aid for JSPS Research Fellow 18J01312; JSPS KAKANHI 20H01720 / Japan Society for the Promotion of Science (http://dx.doi.org/10.13039/501100001691)
- Language
- English
- Date published
- 2022
- Academic Unit
- Psychological and Quantitative Foundations
- Record Identifier
- 9984371300702771
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