Abstract
We analyze the AneuRisk65 curvature functions using a likelihood-based warping method for sparsely sampled curves, and combine it with logistic regression in order to discriminate subjects with aneurysms at or after the terminal bifurcation of the internal carotid artery (the most life-threatening) from subjects with no aneurysms or aneurysms along the carotid artery (the less serious). Significantly lower misclassification rates are obtained when the warping functions are included in the logistic discrimination model, rather than being treated as mere nuisance parameters.
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