News:

• (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.

What is lavaan?

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/

First impression

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)