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Description

Model BIC Posterior Probability.

Fits the neighboring models of a fitted structural equation model and assesses the model uncertainty of the fitted model based on BIC posterior probabilities, using the method presented in Wu, Cheung, and Leung (2020) <doi:10.1080/00273171.2019.1574546>.

Lifecycle: stable Project Status: Active - The project has reached a stable, usable state and is being actively developed. CRAN status CRAN: Release Date Code size Last Commit at Main R-CMD-check

modelbpp: Model BIC Posterior Probability

(Version 0.1.3 updated on 2024-02-20, release history)

This package is for assessing model uncertainty in structural equation modeling (SEM) by the BIC posterior probabilities of the fitted model and its neighboring models, based on the method presented in Wu, Cheung, and Leung (2020). The package name, modelbpp, stands for modelbayesian posterior probability.

  • Wu, H., Cheung, S. F., & Leung, S. O. (2020). Simple use of BIC to assess model selection uncertainty: An illustration using mediation and moderation models. Multivariate Behavioral Research, 55(1), 1--16. https://doi.org/10.1080/00273171.2019.1574546

Homepage

For more information on this package, please visit its GitHub page:

https://sfcheung.github.io/modelbpp/

Installation

The stable CRAN version can be installed by install.packages():

install.packages("modelbpp")

The latest developmental-but-stable version of this package can be installed by remotes::install_github:

remotes::install_github("sfcheung/modelbpp")

Issues

If you have any suggestions or found any bugs, please feel feel to open a GitHub issue. Thanks.

https://github.com/sfcheung/modelbpp/issues.

Metadata

Version

0.1.3

License

Unknown

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