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Clinical Chemistry, Vol 38, 364-369, Copyright © 1992 by American Association for Clinical Chemistry
CA Parvin
Department of Pathology, Washington University School of Medicine, St. Louis, MO 63110.
This paper continues an investigation into the merits of an alternative approach to the statistical evaluation of quality-control rules. In this report, computer simulation is used to evaluate and compare quality-control rules designed to detect increases in within-run or between-run imprecision. When out-of-control conditions are evaluated in terms of their impact on total analytical imprecision, the error detection ability of a rule depends on the relative magnitudes of the between-run and within-run error components under stable operating conditions. A recently proposed rule based on the F-test, designed to detect increases in between-run imprecision, is shown to have relatively poor performance characteristics. Additionally, several issues are examined that have been difficult to address with the traditional evaluation approach.
The following articles in journals at HighWire Press have cited this article:
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J. O. Westgard and B. Stein Automated Selection of Statistical Quality-Control Procedures to Assure Meeting Clinical or Analytical Quality Requirements Clin. Chem., February 1, 1997; 43(2): 400 - 403. [Full Text] [PDF] |
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