Skip to main content

Posterior bimodality in the balanced one-way random-effects model

Buy Article:

$51.00 plus tax (Refund Policy)

Abstract:

Summary.

Although some researchers have examined posterior multimodality for specific richly parameterized models, multimodality is not well characterized for any such model. The paper characterizes bimodality of the joint and marginal posteriors for a conjugate analysis of the balanced one-way random-effects model with a flat prior on the mean. This apparently simple model has surprisingly complex and even bizarre mode behaviour. Bimodality usually arises when the data indicate a much larger between-groups variance than does the prior. We examine an example in detail, present a graphical display for describing bimodality and use real data sets from a statistical practice to shed light on the practical relevance of bimodality for these models.

Keywords: Bayesian analysis; Bimodality; Hierarchical model; Prior distribution; Random effects; Variance components

Document Type: Research Article

DOI: https://doi.org/10.1111/1467-9868.00384

Affiliations: 1: Minneapolis Medical Research Foundation, USA 2: University of Minnesota, Minneapolis, USA

Publication date: 2003-02-01

  • Access Key
  • Free ContentFree content
  • Partial Free ContentPartial Free content
  • New ContentNew content
  • Open Access ContentOpen access content
  • Partial Open Access ContentPartial Open access content
  • Subscribed ContentSubscribed content
  • Partial Subscribed ContentPartial Subscribed content
  • Free Trial ContentFree trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more