Beta-Binomial Statistical Model for Validation Studies of Analytes with a Binary Response.

Abstract

The probability of detection (POD) model has had widespread application for statistically analyzing single and multiple collaborator validations studies with binary outcome data for a wide range of analytes over the last decade. The POD model is placed on a firm theoretical foundation, and extended to a more generalized beta-binomial model. The POD model is revisited and embedded in the beta-binomial model. This generalization includes collaborator reproducibility as a specific parameter. The new model includes only two distributional parameters: the overall across-collaborator probability of detection (LPOD) and the intraclass correlation of collaborators (ICC), measuring irreproducibility. Differences between methods are measured by the difference in LPOD values, denoted dLPOD. Accurate statistical estimators and confidence intervals are provided with validation by simulation. This new beta-binomial model will be applicable to a full range of candidate methods giving binary qualitative results, including microbiological, toxin, allergen, biothreat, and botanical analytes. The new beta-binomial model provides easy equivalence tests to show the study clearly demonstrates (with 95% confidence) that the method differences and collaborator reproducibility are acceptable. The validation system for qualitative binary methods using probability of detection (POD) of an analyte as the parameter of interest has been modified and further validated.