The DOI matches its Crossref record.
Test Reliability Estimated by Analysis of Variance
Abstract
A formula for estimating the reliability of a test, based on the analysis of variance theory, is developed and illustrated. The data needed for the required computation are the number of correct responses to each item and the score for each subject. The results obtained from this formula are identical with those from one of the special cases of the Kuder-Richardson formulation. The relationships of the new procedure to other approaches to the problem are indicated.
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Citations
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Sijtsma, K. (2009) · Psychometrika · doi:10.1007/s11336-008-9101-0 · Cited by 2,814
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Guttman, L. (1945) · Psychometrika · doi:10.1007/bf02288892 · Cited by 1,122
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Campbell, D. T. (1963) · Psychology: A study of a science. Study II. Empirical substructure and relations with other sciences. Volume 6. Investigations of man as socius: Their place in psychology and the social sciences. · doi:10.1037/10590-003 · Cited by 514
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Kelley, K., & Pornprasertmanit, S. (2016) · Psychological Methods · doi:10.1037/a0040086 · Cited by 259
Komaroff, E. (1997) · Applied Psychological Measurement · doi:10.1177/01466216970214004 · Cited by 94
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Studerus, E. (2012) · University of Zurich · doi:10.5167/uzh-164092 · Cited by 6
Metadata
- Authors
- Hoyt, C.
- Venue
- Psychometrika
- Publisher
- Cambridge University Press (CUP)
- Published
- 1941-06
- Volume
- 6
- Issue
- 3
- Pages
- 153-160
- ISSN
- 0033-3123 (ISSN-L)
- 1860-0980
- OpenAlex
- W2032760400
- Cited by
- 513
- References
- 0
- FWCI
- 3.65
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.