The DOI matches its Crossref record; 69 of the 69 references it cites were found in a registry or an index.
Statistics and the Theory of Measurement
Abstract
Just as there are different interpretations of probability, leading to different kinds of inferential statements and different conclusions about statistical models and questions, so there are different theories of measurement, which in turn may lead to different kinds of statistical model and possibly different conclusions. This has led to much confusion and a long running debate about when different classes of statistical methods may legitimately be applied. This paper outlines the major theories of measurement and their relationships and describes the different kinds of models and hypotheses which may be formulated within each theory. One general conclusion is that the domains of applicability of the two major theories are typically different, and it is this which helps apparent contradictions to be avoided in most practical applications.
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Cites
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Cited by
Ahlgren, P., Jarneving, B., & Rousseau, R. (2003) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.10242 · Cited by 785
Item Response Theory and Clinical Measurement
Reise, S. P., & Waller, N. G. (2009) · Annual Review of Clinical Psychology · doi:10.1146/annurev.clinpsy.032408.153553 · Cited by 719
Measurement and Meaning in Biology
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Assumptions of Multiple Regression: Correcting Two Misconceptions
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GUIDELINES TO STATISTICAL EVALUATION OF DATA FROM RATING SCALES AND QUESTIONNAIRES
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Metadata
- Authors
- Hand, D. J.
- Venue
- Journal of the Royal Statistical Society. Series A (Statistics in Society)
- Publisher
- Oxford University Press (OUP)
- Published
- 1996
- Volume
- 159
- Issue
- 3
- Pages
- 445
- ISSN
- 0964-1998 (ISSN-L)
- OpenAlex
- W2091560105
- Cited by
- 263
- References
- 69
- FWCI
- 4.52
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
