Multivariate multidistance tests for high-dimensional low sample size case-control studies
A class of multivariate tests for case‐control studies with high‐dimensional low sample size data and with complex dependence structure, which are common in medical imaging and molecular biology, is proposed. The tests can be applied when the number of variables is much larger than the number of sub...
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          | Published in | Statistics in medicine Vol. 34; no. 9; pp. 1511 - 1526 | 
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| Main Author | |
| Format | Journal Article | 
| Language | English | 
| Published | 
        England
          Blackwell Publishing Ltd
    
        30.04.2015
     Wiley Subscription Services, Inc  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 0277-6715 1097-0258 1097-0258  | 
| DOI | 10.1002/sim.6418 | 
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| Summary: | A class of multivariate tests for case‐control studies with high‐dimensional low sample size data and with complex dependence structure, which are common in medical imaging and molecular biology, is proposed. The tests can be applied when the number of variables is much larger than the number of subjects and when the underlying population distributions are heavy‐tailed or skewed. As a motivating application, we consider a case‐control study where phase‐contrast cinematic cardiovascular magnetic resonance imaging has been used to compare many cardiovascular characteristics of young healthy smokers and young healthy non‐smokers. The tests are based on the combination of tests on interpoint distances. It is theoretically proved that the tests are exact, unbiased and consistent. It is shown that the tests are very powerful under normal, heavy‐tailed and skewed distributions. The tests can also be applied to case‐control studies with high‐dimensional low sample size data from other medical imaging techniques (like computed tomography or X‐ray radiography), chemometrics and microarray data (proteomics and transcriptomics). Copyright © 2015 John Wiley & Sons, Ltd. | 
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| Bibliography: | ArticleID:SIM6418 ark:/67375/WNG-0KVKKRJG-3 istex:78CA43A0987E33378F1786BAACAE6E80917221D2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23  | 
| ISSN: | 0277-6715 1097-0258 1097-0258  | 
| DOI: | 10.1002/sim.6418 |