ts-AUC, a new non-parametric multivariate two-sample test, detects posturographic differences between fallers and non-fallers in Parkinsonian syndromes where adjusted univariate tests do not.
Rectangular confidence regions for the means of multivariate normal distributions
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Revealing posturographic features associated with the risk of falling in patients with Parkinsonian syndromes via machine learning
ts-AUC, a new non-parametric multivariate two-sample test, detects posturographic differences between fallers and non-fallers in Parkinsonian syndromes where adjusted univariate tests do not.