Journal
ANNALS OF APPLIED STATISTICS
Volume 10, Issue 1, Pages 198-218Publisher
INST MATHEMATICAL STATISTICS
DOI: 10.1214/15-AOAS886
Keywords
Persistent homology; statistics; angiography; tree-structured data; topological data analysis
Categories
Funding
- NSF [DMS-1001437]
- NSF Research Training Grant [NSF-DMS-1045133]
- NIMH [2T32MH014235]
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1001437] Funding Source: National Science Foundation
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New representations of tree-structured data objects, using ideas from topological data analysis, enable improved statistical analyses of a population of brain artery trees. A number of representations of each data tree arise from persistence diagrams that quantify branching and looping of vessels at multiple scales. Novel approaches to the statistical analysis, through various summaries of the persistence diagrams, lead to heightened correlations with covariates such as age and sex, relative to earlier analyses of this data set. The correlation with age continues to be significant even after controlling for correlations from earlier significant summaries.
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