knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-" )
The package tidySEM
provides a 'tidy' workflow for conducting, reporting, and plotting structural equation modeling analyses. It does not perform model estimation, but instead allows users to estimate models in a software-agnostic way, using either the free open source R packages lavaan
or OpenMx
, or the commercial closed-source program Mplus
(controlled through the R package MplusAutomation
). The aim of tidySEM
is to provide three specific functions:
OpenMx
These functions are designed with the tidy tools manifesto (Wickham, last updated 23-11-2019) in mind, and interface with the existing suite of packages in the tidyverse
.
You can install the public release of tidySEM
from CRAN with:
install.packages("tidySEM")
If you want access to the latest developer version,
including features that may not yet be finalized,
you can install the development version of tidySEM
from R-universe with:
install.packages('tidySEM', repos = c('https://cjvanlissa.r-universe.dev', 'https://cloud.r-project.org'))
And if you are a developer and want to contribute to tidySEM
,
or want to install a specific historical version of the package,
you can install directly from GitHub with:
install.packages("remotes") remotes::install_github('cjvanlissa/tidySEM')
Every user-facing function in the package is documented, and the documentation can be accessed by running ?function_name
in the R console, e.g., ?graph_sem
.
Furthermore, there are three main vignettes, describing the three main tracks of tidySEM
functions:
You can cite the R-package with the following citation:
Van Lissa, C. J., (2019). tidySEM: Tidy structural equation modeling. R package version 0.2.1. https://github.com/cjvanlissa/tidySEM/
To cite the latent class analysis functionality in tidySEM, cite:
Van Lissa, C. J., Garnier-Villarreal, M., & Anadria, D. (2023). Recommended Practices in Latent Class Analysis using the Open-Source R-Package tidySEM. Structural Equation Modeling. https://doi.org/10.1080/10705511.2023.2250920
If you have ideas, please get involved. You can contribute by opening an issue on 'GitHub', or sending a pull request with proposed features (see further instructions below).
By participating in this project, you agree to abide by the Contributor Covenant.
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