Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 428385, 8 pages
Research Article

Group Factor Analysis for Alzheimer’s Disease

Institute of Statistical Science, Academia Sinica, Taipei 11529, Taiwan

Received 21 December 2012; Accepted 18 January 2013

Academic Editor: Kumar Durai

Copyright © 2013 Wei-Chen Cheng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


For any neuroimaging study in an institute, brain images are normally acquired from healthy controls and patients using a single track of protocol. Traditionally, the factor analysis procedure analyzes image data for healthy controls and patients either together or separately. The former unifies the factor pattern across subjects and the latter deals with measurement errors individually. This paper proposes a group factor analysis model for neuroimaging applications by assigning separate factor patterns to control and patient groups. The clinical diagnosis information is used for categorizing subjects into groups in the analysis procedure. The proposed method allows different groups of subjects to share a common covariance matrix of measurement errors. The empirical results show that the proposed method provides more reasonable factor scores and patterns and is more suitable for medical research based on image data as compared with the conventional factor analysis model.