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Nonparametric assessment of toxicologic assay linearity by bootstrap analysis
G C Critchfield1, D G Wilkins, D L Loughmiller
1Department of Pathology, Utah Valley Regional Medical Center, Provo 84603.
Journal of Analytical Toxicology
|March 1, 1992
Summary
This study introduces bootstrap analysis for validating calibration in toxicologic assays. This method provides a reliable confidence measure for calibration curve linearity, even with unknown error distributions.
Area of Science:
- Toxicology
- Analytical Chemistry
- Biostatistics
Background:
- Calibration is crucial for accurate toxicologic assay evaluation.
- Traditional methods often rely on assumptions about error distribution, limiting applicability.
- Gas chromatography/mass spectrometry (GC/MS) is a common analytical technique.
Purpose of the Study:
- To present a novel approach for validating calibration in toxicologic assays.
- To demonstrate the utility of bootstrap analysis for assessing calibration curve linearity.
- To address limitations of parametric assumptions in error distribution analysis.
Main Methods:
- Application of bootstrap analysis for calibration validation.
- Illustration using a quantitative assay for benzoylecgonine in urine.
- Utilizing gas chromatography/mass spectrometry (GC/MS) for analysis.
Main Results:
- Bootstrap analysis provides a probabilistic measure of confidence in calibration curve linearity.
- The method is effective even when parametric distributions of response errors are unknown.
- Successful application in a benzoylecgonine urine assay.
Conclusions:
- Bootstrap analysis offers a robust and versatile method for calibration validation in toxicology.
- This approach enhances the reliability of toxicologic assay methodology.
- It expands the applicability of calibration validation to diverse error distributions.