Bain: a program for Bayesian testing of order constrained hypotheses in structural equation models

  • Xin Gu*
  • , Herbert Hoijtink
  • , Joris Mulder
  • , Yves Rosseel
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

This paper presents a new statistical method and accompanying software for the evaluation of order constrained hypotheses in structural equation models (SEM). The method is based on a large sample approximation of the Bayes factor using a prior with a data-based correlational structure. An efficient algorithm is written into an R package to ensure fast computation. The package, referred to as Bain, is easy to use for applied researchers. Two classical examples from the SEM literature are used to illustrate the methodology and software.

Original languageEnglish
Pages (from-to)1526-1553
Number of pages28
JournalJournal of Statistical Computation and Simulation
Volume89
Issue number8
DOIs
StatePublished - 24 May 2019

Keywords

  • Approximate Bayesian procedure
  • Bayes factors
  • order constrained hypothesis
  • structural equation model

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