Hierarchical Graphical Bayesian Models In Psychology

CAMPITELLI, GUILLERMO; MACBETH, GUILLERMO

REVISTA COLOMBIANA DE ESTADíSTICA

UNIV NAC COLOMBIA

Lugar: Medellín; Año: 2014 vol. 37 p. 319 - 339

0120-1751

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 can improve the use of powerful hierarchical Bayesian graphical models in psychology.