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http://hdl.handle.net/10071/10568
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Title: Connections between graphical gaussian models and factor analysis
Authors: Salgueiro, M.F.
Smith, P.W.F
McDonald, J. W.
Issue Date: 2010
Publisher: Psychology Press Ltd/Taylor & Francis
Abstract: Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations for the single-factor graphical Gaussian model are facilitated by expressing the manifest partial correlations as functions of the factor partial correlations. The power of selecting a graphical Gaussian model with an association structure between manifest variables compatible with a single-factor model is investigated. The results are illustrated using 2 examples: the 1st is a hypothetical factor model with parallel measures. The 2nd uses data from the British Household Panel Survey on job satisfaction.
Description: WOS:000276098300005 (Nº de Acesso Web of Science)
Peer reviewed: Sim
URI: https://ciencia.iscte-iul.pt/public/pub/id/9479
http://hdl.handle.net/10071/10568
ISSN: 0027-3171
Publisher version: The definitive version is available at: http://dx.doi.org/10.1080/00273170903504851
Appears in Collections:BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica

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