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Revista Colombiana de Estadística
versión impresa ISSN 0120-1751
Resumen
CAMPITELLI, GUILLERMO y MACBETH, GUILLERMO. Hierarchical Graphical Bayesian Models in Psychology. Rev.Colomb.Estad. [online]. 2014, vol.37, n.2, pp.319-339. ISSN 0120-1751. https://doi.org/10.15446/rce.v37n2spe.47940.
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.
Palabras clave : Visual Statistics; GraphicalModels; Bayesian Statistics; Hierarchical Models; Psychology; StatisticalCognition.