Bayesian estimation of circumplex models subject to prior theory constraints and scale-usage bias

Peter Lenk*, Michel Wedel, Ulf Böckenholt

*Corresponding author for this work

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

This paper presents a hierarchical Bayes circumplex model for ordinal ratings data. The circumplex model was proposed to represent the circular ordering of items in psychological testing by imposing inequalities on the correlations of the items. We provide a specification of the circumplex, propose identifying constraints and conjugate priors for the angular parameters, and accommodate theory-driven constraints in the form of inequalities. We investigate the performance of the proposed MCMC algorithm and apply the model to the analysis of value priorities data obtained from a representative sample of Dutch citizens.

Original languageEnglish (US)
Pages (from-to)33-55
Number of pages23
JournalPsychometrika
Volume71
Issue number1
DOIs
StatePublished - Mar 2006

Keywords

  • Bayesian inference
  • Circumplex correlations
  • Inequality constraints
  • Latent variables
  • Ordinal scales

ASJC Scopus subject areas

  • Psychology(all)
  • Applied Mathematics

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