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Visualizing multivariate dependencies with association chain graphs

Höfler, M. and Brückl, T. and Bittner, A. and Lieb, R.. (2007) Visualizing multivariate dependencies with association chain graphs. Methodology, Vol. 3, H. 1. pp. 24-34.

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Official URL: http://edoc.unibas.ch/dok/A5253180

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Abstract

In a recent paper, a new type of graph to visualize the results from graphical models was proposed. Association chain graphs (ACGs) provide a richer visualization than conventional graphs (directed acyclic and recursive regression graphs) if the data can be described with only a small number of parameters. ACGs display not only which associations reach statistical significance, but also the magnitude of associations (confidence intervals for statistical main effects) as the contrast color to the background color of the graph. In this paper, the ACG visualization is extended especially for the case where all variables are binary by illustrating their relative frequencies. This shows the degrees of associations not only on the individual (as expressed by odds ratios or other indexes of association) but also on the community level. We applied the approach to an extensive example of birth and childhood factors for the onset of affective mental disorders using data from the EDSP (Early Developmental Stages of Psychopathology) Study.
Faculties and Departments:07 Faculty of Psychology > Departement Psychologie > Forschungsbereich Klinische Psychologie und Neurowissenschaften > Klinische Psychologie und Epidemiologie (Lieb)
UniBasel Contributors:Lieb, Roselind
Item Type:Article, refereed
Article Subtype:Research Article
Bibsysno:Link to catalogue
Publisher:Hogrefe & Huber
ISSN:1614-1881
Note:Publication type according to Uni Basel Research Database: Journal article
Last Modified:22 Mar 2012 14:25
Deposited On:22 Mar 2012 13:43

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