Thurstonian Model for the Difference-from-Control Test

The difference-from-control (DFC) test is one of the sensory discrimination methods, which is applicable to sensory evaluation in some areas including process optimization and quality assessment for foods. Thurstonian models are important and needed for any one of the sensory discrimination methods including the DFC, because it provides a useful sensory measure, Thurstonian discriminal distance, δ or d', which is theoretically independent of methods or scales used for its estimation. This paper originally derives the Thurstonian model and the maximum likelihood estimations of the model parameters for the DFC test based on a folded normal distribution. R codes for estimations and tests of δ or d' are developed and used in the paper.