The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
The Effect of Number of Rating Scale Categories on Levels of Interrater Reliability : A Monte Carlo Investigation
Open accessAbstract
A computer simulation study was designed to in vestigate the extent to which the interrater reliability of a clinical scale is affected by the number of cate gories or scale points (2, 3, 4, ... ,100). Results in dicate that reliability increases steadily up to 7 scale points, beyond which no substantial increases occur, even when the number of scale poirits is increased to as many as 100. These findings hold under the follow ing conditions: (1) The research investigator has insuf ficient a priori knowledge to use as a reliable guide line for deciding on an appropriate number of scale points to employ, and (2) the dichotomous and ordinal categories being considered all have an underlying metric or continuous scale format.
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Cites
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Cited by
Preston, C. C., & Colman, A. M. (2000) · Acta Psychologica · doi:10.1016/s0001-6918(99)00050-5 · Cited by 2,106
Intraclass correlation – A discussion and demonstration of basic features
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Assessing global pain severity by self-report in clinical and health services research
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In Pursuit of Moderation: Nine Common Errors and Their Solutions1
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Self-citation
Metadata
- Authors
- Cicchetti, D. V., Shoinralter, D., & Tyrer, P. J.
- Venue
- Applied Psychological Measurement
- Publisher
- SAGE Publications
- Published
- 1985-03
- Volume
- 9
- Issue
- 1
- Pages
- 31-36
- ISSN
- 0146-6216 (ISSN-L)
- 1552-3497
- OpenAlex
- W2021321064
- Cited by
- 291
- References
- 41
- FWCI
- 1.49
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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- Cicchetti, D. V., Shoinralter, D., & Tyrer, P. J. (1985). The Effect of Number of Rating Scale Categories on Levels of Interrater Reliability : A Monte Carlo Investigation. Applied Psychological Measurement. https://doi.org/10.1177/014662168500900103
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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.