News
Version 0.7.0, introduced a new iteration of the lavaanPlot function, called lavaanPlot2. Check out a new vignette explaining some of the changes here: Improvements to lavaanPlot
Version 0.8.0, is introducing conditional formatting to the lavaanPlot package, using the new formatting function. Check out the new vignette explaining the changes here: Conditional Formatting in LavaanPlot
Background
The lavaan package is an excellent package for structural equation models, and the DiagrammeR package is an excellent package for producing nice looking graph diagrams. As of right now, the lavaan package has no built in plotting functions for models, and the available options from external packages don’t look as nice and aren’t as easy to use as DiagrammeR, in my opinion. Of course, you can use DiagrammeR to build path diagrams for your models, but it requires you to build the diagram specification manually. This package exists to streamline that process, allowing you to plot your lavaan models directly, without having to translate them into the DOT language specification that DiagrammeR uses.
Installation
You can install lavaanPlot from CRAN with:
install.packages("lavaanPlot")You can also install the development version of lavaanPlot from GitHub with:
install.packages("devtools")
devtools::install_github("alishinski/lavaanPlot")Examples
Here’s a quick example using the mtcars data set.
First fit your lavaan model. The package supports plotting lavaan regression relationships and latent variable - indicator relationships.
## This is lavaan 0.6-11
## lavaan is FREE software! Please report any bugs.
library(lavaanPlot)
model <- 'mpg ~ cyl + disp + hp
qsec ~ disp + hp + wt'
fit <- sem(model, data = mtcars)
summary(fit)## lavaan 0.6-11 ended normally after 32 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 9
##
## Number of observations 32
##
## Model Test User Model:
##
## Test statistic 18.266
## Degrees of freedom 2
## P-value (Chi-square) 0.000
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Regressions:
## Estimate Std.Err z-value P(>|z|)
## mpg ~
## cyl -0.987 0.738 -1.337 0.181
## disp -0.021 0.010 -2.178 0.029
## hp -0.017 0.014 -1.218 0.223
## qsec ~
## disp -0.008 0.004 -2.122 0.034
## hp -0.023 0.004 -5.229 0.000
## wt 1.695 0.398 4.256 0.000
##
## Covariances:
## Estimate Std.Err z-value P(>|z|)
## .mpg ~~
## .qsec 0.447 0.511 0.874 0.382
##
## Variances:
## Estimate Std.Err z-value P(>|z|)
## .mpg 8.194 2.049 4.000 0.000
## .qsec 0.996 0.249 4.000 0.000Then using that model fit object, simply call the lavaanPlot function, specifying your desired graph parameters.
lavaanPlot(model = fit, node_options = list(shape = "box", fontname = "Helvetica"), edge_options = list(color = "grey"), coefs = F)There is also functionality to save these plots as images and embed them in pdf output documents.
model <- 'mpg ~ cyl + disp + hp
qsec ~ disp + hp + wt'
fit <- sem(model, data = mtcars)
pl <- lavaanPlot(model = fit)
# Example for pdf embed
embed_plot_pdf(pl, "plot2.pdf")
# Example for saving to .png
save_png(pl, "plot.png")