¹Edith Cowan University, School of Psychology and Social Science, Mount Lawley, Australia. Lecturer. Email: gjcampitelli@gmail.com
²Universidad Nacional de Entre Ríos, Facultad de Ciencias de la Educación, Argentina. Professor. Email: g.macbeth@conicet.gov.ar

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.

Key words: Visual Statistics, GraphicalModels, Bayesian Statistics, Hierarchical Models, Psychology, StatisticalCognition.

El mejoramiento de los métodos gráficos en la investigación en psicología puede promover su uso y una mejor compresión de su poder de expresión. La aplicación de modelos Bayesianos gráficos jerárquicos se ha vuelto más frecuente en la investigación en psicología. El objetivo de este trabajo es introducir sugerencias para el mejoramiento de los modelos Bayesianos gráficos jerárquicos en psicología. Este conjunto de sugerencias se apoya en la descripción y comparación entre los dos enfoques principales con el uso de notación y pictogramas de distribución. Se concluye que la combinación de los aspectos relevantes de ambos puede mejorar el uso de los modelos Bayesianos gráficos jerárquicos en psicología

Palabras clave: cognición estadística, estadística Bayesiana, estadística visual, modelos gráficos, modelos jerárquicos, psicología.

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