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Positive loadings and factor correlations from positive covariance matrices
 Wim P. Krijnen
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In many instances it is reasonable to assume that the population covariance matrix has positive elements. This assumption implies for the single factor analysis model that the loadings and regression weights for best linear factor prediction are positive. For the multiple factor analysis model where each variable loads on a single factor and a hierarchical factor model, it implies that the loadings and the factor correlations are positive. For the latter model it also implies that the regression weights for first and secondorder factor prediction are positive.
 Title
 Positive loadings and factor correlations from positive covariance matrices
 Journal

Psychometrika
Volume 69, Issue 4 , pp 655660
 Cover Date
 200412
 DOI
 10.1007/BF02289861
 Print ISSN
 00333123
 Online ISSN
 18600980
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Keywords

 Classical test theory
 congeneric tests
 structural equation models
 hierarchical factor analysis
 regression weights
 best linear factor prediction
 Industry Sectors
 Authors

 Wim P. Krijnen ^{(1)}
 Author Affiliations

 1. Department of Psychological Methods, University of Amsterdam, Roetersstraat 15, 1018 WB, Amsterdam, The Netherlands