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

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

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MLA
Gu, Xin, et al. “Bain : A Program for Bayesian Testing of Order Constrained Hypotheses in Structural Equation Models.” JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol. 89, no. 8, 2019, pp. 1526–53.
APA
Gu, X., Hoijtink, H., Mulder, J., & Rosseel, Y. (2019). Bain : a program for Bayesian testing of order constrained hypotheses in structural equation models. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 89(8), 1526–1553.
Chicago author-date
Gu, Xin, Herbert Hoijtink, Joris Mulder, and Yves Rosseel. 2019. “Bain : A Program for Bayesian Testing of Order Constrained Hypotheses in Structural Equation Models.” JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 89 (8): 1526–53.
Chicago author-date (all authors)
Gu, Xin, Herbert Hoijtink, Joris Mulder, and Yves Rosseel. 2019. “Bain : A Program for Bayesian Testing of Order Constrained Hypotheses in Structural Equation Models.” JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 89 (8): 1526–1553.
Vancouver
1.
Gu X, Hoijtink H, Mulder J, Rosseel Y. Bain : a program for Bayesian testing of order constrained hypotheses in structural equation models. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION. 2019;89(8):1526–53.
IEEE
[1]
X. Gu, H. Hoijtink, J. Mulder, and Y. Rosseel, “Bain : a program for Bayesian testing of order constrained hypotheses in structural equation models,” JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, vol. 89, no. 8, pp. 1526–1553, 2019.
@article{8642366,
  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.},
  author       = {Gu, Xin and Hoijtink, Herbert and Mulder, Joris and Rosseel, Yves},
  issn         = {0094-9655},
  journal      = {JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION},
  keywords     = {FORTRAN-90 PROGRAM,INEQUALITY,Approximate Bayesian procedure,Bayes factors,order constrained,hypothesis,structural equation model},
  language     = {eng},
  number       = {8},
  pages        = {1526--1553},
  title        = {Bain : a program for Bayesian testing of order constrained hypotheses in structural equation models},
  url          = {http://dx.doi.org/10.1080/00949655.2019.1590574},
  volume       = {89},
  year         = {2019},
}

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