Critical evaluation of assessor difference correction approaches in sensory analysis

•Correcting for assessor differences can improve estimation of product effects.•ANOVA F-test for some correction methods produces too optimistic p-values.•Permutation approach enables controlling the type I error (false positive) rate.•Mixed assessor model (MAM) is most powerful in detecting product differences.•Unequal reproducibility between assessors affects MAM product effect significance.