Bayesian evaluation of inequality constrained hypotheses

Psychol Methods. 2014 Dec;19(4):511-27. doi: 10.1037/met0000017. Epub 2014 Jul 21.


Bayesian evaluation of inequality constrained hypotheses enables researchers to investigate their expectations with respect to the structure among model parameters. This article proposes an approximate Bayes procedure that can be used for the selection of the best of a set of inequality constrained hypotheses based on the Bayes factor in a very general class of statistical models. The software package BIG is provided such that psychologists can use the approach proposed for the analysis of their own data. To illustrate the approximate Bayes procedure and the use of BIG, we evaluate inequality constrained hypotheses in a path model and a logistic regression model. Two simulation studies on the performance of our approximate Bayes procedure show that it results in accurate Bayes factors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Bayes Theorem*
  • Computer Simulation*
  • Humans
  • Logistic Models*
  • Parent-Child Relations
  • Software*
  • Statistics as Topic