An R package for goodness of fit testing of structural equation models.
Built on top of lavaan
.
Use the following command from inside R
:
# install.packages("remotes")
remotes::install_github("JonasMoss/semTests")
Call the library
function, create a lavaan
model, and run the
pvalues
function.
library("semTests")
model <- "A =~ A1+A2+A3+A4+A5;
C =~ C1+C2+C3+C4+C5"
n <- 200
object <- lavaan::sem(model, psych::bfi[1:n, 1:10], estimator = "MLM")
pvalues(object)
#> ppeba2_trad ppeba4_trad pols_2_trad ppeba2_rls ppeba4_rls pols_2_rls
#> 0.04182486 0.04370615 0.04397064 0.04235143 0.04424139 0.04450873
Foldnes, N., & Grønneberg, S. (2018). Approximating Test Statistics Using Eigenvalue Block Averaging. Structural Equation Modeling, 25(1), 101–114. https://doi.org/10.1080/10705511.2017.1373021
Grønneberg, S., & Foldnes, N. (2019). Testing Model Fit by Bootstrap Selection. Structural Equation Modeling, 26(2), 182–190. https://doi.org/10.1080/10705511.2018.1503543
Marcoulides, K. M., Foldnes, N., & Grønneberg, S. (2020). Assessing Model Fit in Structural Equation Modeling Using Appropriate Test Statistics. Structural Equation Modeling, 27(3), 369–379. https://doi.org/10.1080/10705511.2019.1647785
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02
If you encounter a bug, have a feature request or need some help, open a Github issue. Create a pull requests to contribute.
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