## Abstract

I propose a method for defining tolerance limits for assay bias and assay imprecision, based on the effects of these tolerance limits on the clinical specificity of the assay. An analytical "error budget" is defined as the squared sums of the imprecision and bias errors. The maximum limit for this error budget is set at a value corresponding to a 50% increase in the false-positive rate for classifying healthy subjects. For gaussian distributions with ±2 SD used as decision limits, this error budget equates to 0.45 SD of combined within-person and between-person biological variation (SD_{Biol}). To provide reasonable power for bias detection in an assay, I recommend that the SD of the assay be kept at less than half the bias limit. Then, for the gaussian distribution, the maximum bias limit should be <0.36 SD_{Biol}, and the SD of the assay should be <0.18 SD_{Biol}. Procedures are provided for using the same principles to define tolerance limits for decision limits other than ±2 SD and for nongaussian distributions.

Original language | English (US) |
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Pages (from-to) | 1514-1518 |

Number of pages | 5 |

Journal | Clinical chemistry |

Volume | 39 |

Issue number | 7 |

State | Published - 1993 |

## Keywords

- Analytical performance goals
- Error budget
- Statistics

## ASJC Scopus subject areas

- Medicine(all)