Probability of Identification: A Statistical Model for the Validation of Qualitative Botanical Identification Methods

Author:

LaBudde Robert A1,Harnly James2

Affiliation:

1. Least Cost Formulations, Ltd, 824 Timberlake Dr, Virginia Beach, VA 23464 Old Dominion University, Department of Mathematics and Statistics, Norfolk, VA 23529

2. U.S. Department of Agriculture, Agricultural Research Center, Beltsville Human Nutrition Research Center, Food Composition and Methods Development Laboratory, Bldg 161 BARC-East, Beltsville, MD 20705

Abstract

Abstract A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.

Publisher

Oxford University Press (OUP)

Subject

Pharmacology,Agronomy and Crop Science,Environmental Chemistry,Food Science,Analytical Chemistry

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