(pinned): the 10th European Congress of Methodology (EAM2023) will take pace in Ghent (Belgium) from Tuesday July 11 to Thursday July 13 (2023). Visit the EAM2023 website for more information.
(14 March 2023): slides for my presentation in Bielefeld can be found here.
(14 March 2023): lavaan version 0.6-15 has been released on CRAN. See Version History for more information. This is just a maintenance release.
(9 Feb 2023): An E-learning course on “Structural Equation Modeling in R using lavaan” will be organized at Utrecht University (period: 03-14 July 2023). For information, see the website.
(9 Feb 2023): lavaan version 0.6-14 has been released on CRAN. See Version History for more information.
The lavaan package is developed to provide useRs, researchers and teachers a free open-source, but commercial-quality package for latent variable modeling. You can use lavaan to estimate a large variety of multivariate statistical models, including path analysis, confirmatory factor analysis, structural equation modeling and growth curve models.
The official reference to the lavaan package is the following paper:
Yves Rosseel (2012). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. URL http://www.jstatsoft.org/v48/i02/
To get a first impression of how lavaan works in practice, consider the following example of a SEM model. The figure below contains a graphical representation of the model that we want to fit.
myModel <- ' # latent variables ind60 =~ x1 + x2 + x3 dem60 =~ y1 + y2 + y3 + y4 dem65 =~ y5 + y6 + y7 + y8 # regressions dem60 ~ ind60 dem65 ~ ind60 + dem60 # residual covariances y1 ~~ y5 y2 ~~ y4 + y6 y3 ~~ y7 y4 ~~ y8 y6 ~~ y8 ' fit <- sem(model = myModel, data = PoliticalDemocracy) summary(fit)