Document Detail

SCA with rotation to distinguish common and distinctive information in linked data.
MedLine Citation:
PMID:  23361416     Owner:  NLM     Status:  Publisher    
Often data are collected that consist of different blocks that all contain information about the same entities (e.g., items, persons, or situations). In order to unveil both information that is common to all data blocks and information that is distinctive for one or a few of them, an integrated analysis of the whole of all data blocks may be most useful. Interesting classes of methods for such an approach are simultaneous-component and multigroup factor analysis methods. These methods yield dimensions underlying the data at hand. Unfortunately, however, in the results from such analyses, common and distinctive types of information are mixed up. This article proposes a novel method to disentangle the two kinds of information, by making use of the rotational freedom of component and factor models. We illustrate this method with data from a cross-cultural study of emotions.
Martijn Schouteden; Katrijn Van Deun; Sven Pattyn; Iven Van Mechelen
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-30
Journal Detail:
Title:  Behavior research methods     Volume:  -     ISSN:  1554-3528     ISO Abbreviation:  Behav Res Methods     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-30     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101244316     Medline TA:  Behav Res Methods     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Research Group for Quantitative Psychology and Individual Differences, KU Leuven, Leuven, Belgium,
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