Evaluation of threshold limit methods for sensory data

Current approaches to sensory thresholds, such as geometric means and logistic regression, ignore any formal consideration of uncertainty and variability. Various alternative methods based on approximate confidence and prediction intervals about the logistic regression were examined. All methods tended to provide the same ranking among different analyte/media combinations evaluated. Formal statistical conclusions could be made for thresholds based on interval analyses, but not for geometric mean or logistic regression. Methods based on prediction intervals consistently estimated the highest thresholds. Interval-based methods varied with the level of confidence required, as well as the number of panelists and concentrations tested. The geometric mean method yielded the most consistent estimates across a range of panel sizes.