The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Generation and Application of Data on Biological Variation in Clinical Chemistry
Abstract
Most clinical chemical analytes vary in a random manner around a homeostatic set point. Replicate analyses of a series of specimens collected from a group of subjects allows estimation of analytical, within and between subject components of variation. The preferred experimental procedures and statistical methods for evaluation of data and analysis of variance are described; a detailed example is provided in the Appendix. The many uses of data on biological variation in clinical chemistry are reviewed, including setting analytical goals, deciding the significance of changes in serial results from an individual, evaluating the utility of conventional population-based reference values in patient management, and other applications.
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Cites
An analysis of variance test for normality (complete samples)
SHAPIRO, S. S., & WILK, M. B. (1965) · Biometrika · doi:10.1093/biomet/52.3-4.591 · Cited by 23,480
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Current databases on biological variation: pros, cons and progress
C. Ricós, V. A. (1999) · Scandinavian Journal of Clinical and Laboratory Investigation · doi:10.1080/00365519950185229 · Cited by 987
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Tracy, R. P., Psaty, B. M., Macy, E., Bovill, E. G., Cushman, M., Cornell, E. S., & Kuller, L. H. (1997) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/01.atv.17.10.2167 · Cited by 539
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Metadata
- Authors
- Fraser, G. G., & Harris, E. K.
- Venue
- Critical Reviews in Clinical Laboratory Sciences
- Publisher
- Informa UK Limited
- Published
- 1989-01
- Volume
- 27
- Issue
- 5
- Pages
- 409-437
- ISSN
- 1040-8363 (ISSN-L)
- 1549-781X
- OpenAlex
- W2117872000
- Cited by
- 870
- References
- 1
- FWCI
- 5.52
- 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.
