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modelbpp: Model BIC Posterior Probability

(Version 0.1.6 updated on 2025-09-24, 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 model bayesian 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

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Version

Install

install.packages('modelbpp')

Monthly Downloads

186

Version

0.1.6

License

GPL (>= 3)

Maintainer

Shu Fai Cheung

Last Published

September 24th, 2025

Functions in modelbpp (0.1.6)

print.partables

Print a partables-Class Object
print.model_set

Print a model_set-Class Object
plot.model_graph

Plot a Network of Models
model_set

BIC Posterior Probabilities of Neighboring Models
min_prior

Minimum Prior
measurement_invariance_models

Measurement Invariance Models
partables_helpers

Helper Functions For partables-Class Objects
print.sem_outs

Print an sem_outs-Class Object
dat_serial_4

A Sample Dataset Based On a Serial Mediation Model (For Testing)
c.partables

Manipulate Parameter Tables
get_drop

Models That Are More Restricted
fit_many

Fit a List of Models
get_add

Models That Are Less Restricted
dat_cfa

A Sample Dataset Based On a Confirmatory Factor Analysis Model (For Testing)
dat_sem

A Sample Dataset Based On a Structural Model (For Testing)
dat_path_model_p06

A Sample Dataset Based On a Complex Path Model (For Testing)
dat_serial_4_weak

A Sample Dataset Based On a Serial Mediation Model With Weak Paths (For Testing)
model_set_combined

Two or More Hypothesized Models
dat_path_model

A Sample Dataset Based on a Path Model (For Testing)
model_graph

Generate a Graph of Models
modelbpp-package

modelbpp: Model BIC Posterior Probability