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

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.

Keywords:

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

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

Herbert Hoijtink is supported by the Netherlands Organization for Scientific Research (NWO grant number 024.001.003). Joris Mulder was supported by a Vidi Grant of the Netherlands Organization of Scientific Research (NWO grant number 452-17-006).