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Clinical Chemistry 37: 26-29, 1991;
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Clinical Chemistry, Vol 37, 26-29, Copyright © 1991 by American Association for Clinical Chemistry

Multi-factor designs. IV. How multi-factor designs improve the estimate of total error by accounting for protocol-specific biases

JS Krouwer
Ciba Corning Diagnostics Corp., Medfield, MA 02052.

Total error is often calculated as a combination of random error and fixed bias. However, the specific protocols used to estimate random error and fixed bias are themselves variable factors that can affect the estimate of total error. We refer to biases such as assay drift, sample-to-sample carryover, and reagent carryover as examples of fixed biases that are protocol-specific and distinguish them from other fixed biases. Failing to account for protocol-specific biases that are present will lead to incorrect estimates of total error when routine use of the assay involves a protocol different from that used to estimate total error. Multi-factor protocols are recommended to determine protocol-specific biases, which, if present, should be included in the estimate of total error.


The following articles in journals at HighWire Press have cited this article:


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J. S. Krouwer
Setting Performance Goals and Evaluating Total Analytical Error for Diagnostic Assays
Clin. Chem., June 1, 2002; 48(6): 919 - 927.
[Abstract] [Full Text] [PDF]

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J. S. Krouwer
How to Improve Total Error Modeling by Accounting for Error Sources Beyond Imprecision and Bias
Clin. Chem., July 1, 2001; 47(7): 1329 - 1330.
[Full Text] [PDF]


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Copyright © 1991 by the American Association for Clinical Chemistry.