Hierarchical Bayesian Modeling: Does it Improve Parameter Stability?

Benjamin Scheibehenne, Thorsten Pachur

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Fitting multi-parameter models to the behavior of individual participants is a popular approach in cognitive science to measuring individual differences. This approach assumes that the model parameters capture psychologically meaningful and stable characteristics of a person. If so, the estimated parameters should show, to some extent, stability across time. Recently, it has been proposed that hierarchical procedures might provide more reliable parameter estimates than non-hierarchical procedures. Here, we examine the benefits of hierarchical parameter estimation for assessing parameter stability using Bayesian techniques. Using the transfer-of-attention-exchange model (TAX; Birnbaum & Chavez, 1997), a highly successful account of risky decision making, we compare parameter stability based on hierarchically versus non-hierarchically estimated parameters. Surprisingly, we find that parameter stability for TAX is not improved by using a hierarchical Bayesian as compared to a non-hierarchical Bayesian approach. Further analyses suggest that this is because the shrinkage induced by hierarchical estimation overcorrects for extreme yet reliable parameter values. We suggest that the benefits of hierarchical techniques may be limited to particular conditions, such as sparse data on the individual level or very homogenous samples.

Original languageEnglish
Title of host publicationCooperative Minds
Subtitle of host publicationSocial Interaction and Group Dynamics - Proceedings of the 35th Annual Meeting of the Cognitive Science Society, CogSci 2013
EditorsMarkus Knauff, Natalie Sebanz, Michael Pauen, Ipke Wachsmuth
PublisherThe Cognitive Science Society
Pages1277-1282
Number of pages6
ISBN (Electronic)9780976831891
StatePublished - 2013
Externally publishedYes
Event35th Annual Meeting of the Cognitive Science Society - Cooperative Minds: Social Interaction and Group Dynamics, CogSci 2013 - Berlin, Germany
Duration: 31 Jul 20133 Aug 2013

Publication series

NameCooperative Minds: Social Interaction and Group Dynamics - Proceedings of the 35th Annual Meeting of the Cognitive Science Society, CogSci 2013

Conference

Conference35th Annual Meeting of the Cognitive Science Society - Cooperative Minds: Social Interaction and Group Dynamics, CogSci 2013
Country/TerritoryGermany
CityBerlin
Period31/07/133/08/13

Keywords

  • cognitive modeling
  • hierarchical Bayesian modeling
  • parameter consistency
  • risky choice
  • transfer-of-attention-exchange model

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