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

Xin Gu*, Herbert Hoijtink, Joris Mulder, Y. Rosseel

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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
JournalJournal of Statistical Computation and Simulation
Volume89
Issue number8
DOIs
Publication statusPublished - 2019

Fingerprint

Structural Equation Model
Bayes Factor
Testing
Software
Statistical method
Statistical methods
Efficient Algorithms
Methodology
Evaluation
Approximation
Structural equation model
Bayes factor

Keywords

  • Approximate Bayesian procedure
  • Bayes factors
  • FORTRAN-90 PROGRAM
  • INEQUALITY
  • order constrained hypothesis
  • structural equation model

Cite this

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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.",
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Bain : A program for Bayesian testing of order constrained hypotheses in structural equation models. / Gu, Xin; Hoijtink, Herbert; Mulder, Joris; Rosseel, Y.

In: Journal of Statistical Computation and Simulation, Vol. 89, No. 8, 2019, p. 1526-1553.

Research output: Contribution to journalArticleScientificpeer-review

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T2 - A program for Bayesian testing of order constrained hypotheses in structural equation models

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AU - Hoijtink, Herbert

AU - Mulder, Joris

AU - Rosseel, Y.

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