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Export Reference (APA) 
Salgueiro, M.F., Smith, P.W.F & McDonald, J. W. (2010). Connections between graphical gaussian models and factor analysis. Multivariate Behavioral Research. 45 (1), 135-152
Export Reference (IEEE) 
M. D. Salgueiro et al.,  "Connections between graphical gaussian models and factor analysis", in Multivariate Behavioral Research, vol. 45, no. 1, pp. 135-152, 2010
Export BibTeX 
@article{salgueiro2010_1765575948873,
	author = "Salgueiro, M.F. and Smith, P.W.F and McDonald, J. W.",
	title = "Connections between graphical gaussian models and factor analysis",
	journal = "Multivariate Behavioral Research",
	year = "2010",
	volume = "45",
	number = "1",
	doi = "10.1080/00273170903504851",
	pages = "135-152",
	url = "http://www.tandfonline.com/doi/pdf/10.1080/00273170903504851"
}
Export RIS 
TY  - JOUR
TI  - Connections between graphical gaussian models and factor analysis
T2  - Multivariate Behavioral Research
VL  - 45
IS  - 1
AU  - Salgueiro, M.F.
AU  - Smith, P.W.F
AU  - McDonald, J. W.
PY  - 2010
SP  - 135-152
SN  - 0027-3171
DO  - 10.1080/00273170903504851
UR  - http://www.tandfonline.com/doi/pdf/10.1080/00273170903504851
AB  - 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.
ER  -