This paper describes a more efficient paired comparison method that reduces the number of trials necessary for converting a table of paired comparisons into scaler data. Instead of comparing every pair of samples (the complete method), a partial method is used that makes more comparisons between closer samples than between more distant samples. A sorting algorithm is used to efficiently order the samples with paired comparisons, and each comparison is recorded. When the sorting is completed, more trials will have been conducted between closer samples than between distant samples. Regression is used to scale the resulting comparison matrix into a one dimensional perceptual quality estimate.