SciELO - Scientific Electronic Library Online

 
vol.37 issue2Exploring the Mobile Structural Assessment Tool: Concept Maps for Learning WebsiteGraphical Tools to Assess Goodness-of-Fit in Non-Location-Scale Distributions author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • On index processCited by Google
  • Have no similar articlesSimilars in SciELO
  • On index processSimilars in Google

Share


Revista Colombiana de Estadística

Print version ISSN 0120-1751

Abstract

CAMPITELLI, GUILLERMO  and  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.

Keywords : Visual Statistics; GraphicalModels; Bayesian Statistics; Hierarchical Models; Psychology; StatisticalCognition.

        · abstract in Spanish     · text in English     · English ( pdf )