blavaan: Bayesian Latent Variable Analysis

Fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models. References: Merkle & Rosseel (2018) <doi:10.18637/jss.v085.i04>; Merkle et al. (2021) <doi:10.18637/jss.v100.i06>.

Version: 0.4-3
Depends: R (≥ 3.5.0), methods, lavaan (≥ 0.6-10), Rcpp (≥ 0.12.15)
Imports: stats, utils, graphics, coda, mnormt, nonnest2 (≥ 0.5-5), loo (≥ 2.0), rstan (≥ 2.21.2), rstantools (≥ 1.5.0), RcppParallel (≥ 5.0.1), bayesplot, Matrix, future.apply, tmvnsim
LinkingTo: StanHeaders (≥ 2.18.1), rstan (≥ 2.21.2), BH (≥ 1.69.0), Rcpp (≥ 0.12.15), RcppEigen (≥ 0.3.3.4.0), RcppParallel (≥ 5.0.1)
Suggests: runjags (≥ 2.0.4-4), modeest (≥ 2.3.3), rjags, cmdstanr, semTools, tinytest
Published: 2022-05-11
Author: Edgar Merkle ORCID iD [aut, cre], Yves Rosseel [aut], Ben Goodrich [aut], Mauricio Garnier-Villarreal ORCID iD [ctb] (R/blav_compare.R, R/ctr_bayes_fit.R, vignettes/approx_fi.Rmd), Terrence D. Jorgensen ORCID iD [ctb] (R/ctr_bayes_fit.R, R/ctr_ppmc.R, R/blav_predict.R), Huub Hoofs [ctb] (R/ctr_bayes_fit.R), Rens van de Schoot [ctb] (R/ctr_bayes_fit.R), Andrew Johnson [ctb] (Makevars), Matthew Emery [ctb] (loo moment_match)
Maintainer: Edgar Merkle <merklee at missouri.edu>
License: GPL (≥ 3)
NeedsCompilation: yes
SystemRequirements: GNU make
Additional_repositories: https://mc-stan.org/r-packages/
Citation: blavaan citation info
Materials: README NEWS
In views: Bayesian, Psychometrics
CRAN checks: blavaan results

Documentation:

Reference manual: blavaan.pdf

Downloads:

Package source: blavaan_0.4-3.tar.gz
Windows binaries: r-devel: blavaan_0.4-3.zip, r-release: blavaan_0.4-3.zip, r-oldrel: blavaan_0.4-3.zip
macOS binaries: r-release (arm64): blavaan_0.4-3.tgz, r-oldrel (arm64): blavaan_0.4-3.tgz, r-release (x86_64): blavaan_0.4-3.tgz, r-oldrel (x86_64): blavaan_0.4-3.tgz
Old sources: blavaan archive

Reverse dependencies:

Reverse depends: brxx, Replication
Reverse imports: tidySEM
Reverse suggests: bayestestR, insight, performance, semTools

Linking:

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