Product maps for ranked preference data

Abstract

For randomized block and balanced incomplete block designs, nonparametric treatment comparisons are usually made using the usual Friedman and Durbin tests and the multiple-comparisons approach. This permits an assessment of only the mean rankings. Such comparisons are here extended to permit linear (mean) and quadratic assessments simultaneously by the use of product maps incorporating confidence circles. If the blocks are judges or consumers then differences in quadratic effects can indicate product differences in consensus or market segmentation.