A class of multivariate tests for case-control studies with high-dimensional low sample size data and with complex dependence structure, whichare 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).

Multivariate multidistance tests for high-dimensional low sample size case-control studies

MAROZZI, Marco
Primo
2015

Abstract

A class of multivariate tests for case-control studies with high-dimensional low sample size data and with complex dependence structure, whichare 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).
2015
Marozzi, Marco
File in questo prodotto:
File Dimensione Formato  
SIM.pdf

solo gestori archivio

Descrizione: versione editoriale
Tipologia: Full text (versione editoriale)
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 208.51 kB
Formato Adobe PDF
208.51 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2525951
Citazioni
  • ???jsp.display-item.citation.pmc??? 6
  • Scopus 38
  • ???jsp.display-item.citation.isi??? 37
social impact