Testing for statistically significant differences between groups of scan patterns

Abstract

Pairwise sequence alignment methods are now often used when analyzing eyetracking data [Hacisalihzade et al. 1992; Brandt and Stark 1997; Josephson and Holmes 2002, 2006; Pan et al. 2004; Heminghous and Duchowski 2006]. While optimal sequence alignment scores provide a valuation of similarity and difference, they do not readily provide a statistical test of similarity or difference. Furthermore, pairwise alignment scores cannot be used to compare groups of scan patterns directly. Using a statistic that compiles these pairwise alignment scores, a statistical evaluation of similarity can be made by repeatedly computing scores from different permutations of scan pattern groupings. This test produces a p-value as a level of statistical significance.