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A Study Of Hippocampal Shape Difference Between Genders By Efficient Hypothesis Test And Discriminative Deformation, Luping Zhou, Richard Hartley, Paulette Lieby, Nick Barnes, Kaarin Anstey, Nicolas Cherbuin, Perminder Sachdev

Faculty of Engineering and Information Sciences - Papers: Part A

Hypothesis testing is an important way to detect the statistical difference between two populations. In this paper, we use the Fisher permutation and bootstrap tests to differentiate hippocampal shape between genders. These methods are preferred to traditional hypothesis tests which impose assumptions on the distribution of the samples. An efficient algorithm is adopted to rapidly perform the exact tests. We extend this algorithm to multivariate data by projecting the original data onto an "informative direction" to generate a scalar test statistic. This "informative direction" is found to preserve the original discriminative information. This direction is further used in this paper …