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Hierarchical Bayesian Graphical Models in Psychology

Campitelli, G. and Macbeth, G. (2014) Hierarchical Bayesian Graphical Models in Psychology. Revista Colombiana de Estadistica, 37 (2). pp. 319-339.

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Link to Published Version: https://doi.org/10.15446/rce.v37n2spe.47940
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Abstract

The improvement of graphical methods in psychological research can promote their use and a better comprehension of their expressive power. The application of hierarchical Bayesian graphical models has recently become more frequent in psychological research. The aim of this contribution is to introduce suggestions for the improvement of hierarchical Bayesian graphical models in psychology. This novel set of suggestions stems from the description and comparison between two main approaches concerned with the use of plate notation and distribution pictograms. It is concluded that the combination of relevant aspects of both models might improve the use of powerful hierarchical Bayesian graphical models in psychology.

Item Type: Journal Article
Publisher: Universidad Nacional de Colombia
URI: http://researchrepository.murdoch.edu.au/id/eprint/53787
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