Literature DB >> 26221671

Group Testing for Longitudinal Data.

Yi Hong, Nikhil Singh, Roland Kwitt, Marc Niethammer.   

Abstract

We consider how to test for group differences of shapes given longitudinal data. In particular, we are interested in differences of longitudinal models of each group's subjects. We introduce a generalization of principal geodesic analysis to the tangent bundle of a shape space. This allows the estimation of the variance and principal directions of the distribution of trajectories that summarize shape variations within the longitudinal data. Each trajectory is parameterized as a point in the tangent bundle. To study statistical differences in two distributions of trajectories, we generalize the Bhattacharyya distance in Euclidean space to the tangent bundle. This not only allows to take second-order statistics into account, but also serves as our test-statistic during permutation testing. Our method is validated on both synthetic and real data, and the experimental results indicate improved statistical power in identifying group differences. In fact, our study sheds new light on group differences in longitudinal corpus callosum shapes of subjects with dementia versus normal controls.

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Year:  2015        PMID: 26221671     DOI: 10.1007/978-3-319-19992-4_11

Source DB:  PubMed          Journal:  Inf Process Med Imaging        ISSN: 1011-2499


  2 in total

1.  LOCALIZING DIFFERENTIALLY EVOLVING COVARIANCE STRUCTURES VIA SCAN STATISTICS.

Authors:  Ronak Mehta; Hyunwoo J Kim; Shulei Wang; Sterling C Johnson; Ming Yuan; Vikas Singh
Journal:  Q Appl Math       Date:  2018-12-17       Impact factor: 0.815

2.  A geometric framework for statistical analysis of trajectories with distinct temporal spans.

Authors:  Rudrasis Chakraborty; Vikas Singh; Nagesh Adluru; Baba C Vemuri
Journal:  Proc IEEE Int Conf Comput Vis       Date:  2017-12-25
  2 in total

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