The Gaussian Graphical Model in Cross-Sectional and Time-Series Data

We discuss the Gaussian graphical model (GGM; an undirected network of partial correlation coefficients) and detail its utility as an exploratory data analysis tool. The GGM shows which variables predict one-another, allows for sparse modeling of covariance structures, and may highlight potential ca...

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Veröffentlicht in:	Multivariate behavioral research Jg. 53; H. 4; S. 453 - 480
Hauptverfasser:	Epskamp, Sacha, Waldorp, Lourens J., Mõttus, René, Borsboom, Denny
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Routledge 04.07.2018 Taylor & Francis Ltd
Schlagworte:	Between-subjects design Computer Simulation Correlation coefficients Covariance Cross-Sectional Studies Data analysis Data Interpretation, Statistical Datasets Economic models Empirical analysis exploratory-data analysis Humans Mathematical models Models, Statistical multilevel modeling multivariate analysis network modeling Software Surveys and Questionnaires Time Factors Time series Time-series analysis multilevel modeling Time-series analysis exploratory-data analysis network modeling multivariate analysis
ISSN:	0027-3171, 1532-7906, 1532-7906
Online-Zugang:	Volltext
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