A plot() method exists for blavaan objects, with this method making use of the bayesplot package (Gabry and Mahr 2021). We provide details here about how this functionality works. We will use a 3-factor model for demonstration:

HS.model <- ' visual  =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed   =~ x7 + x8 + x9 '

fit <- bcfa(HS.model, data=HolzingerSwineford1939)

### Basics

Because many blavaan models will have many parameters, users generally need to specify which parameters they wish to plot. This is accomplished by supplying numbers to the pars argument, where the numbers correspond to the order of parameters from the coef() command (the numbers also appear in the free column of the parameter table). Users must also specify the type of plot that they desire via the plot.type argument. So, for example, a trace plot of the first four model parameters looks like

plot(fit, pars = 1:4, plot.type = "trace")

Many other plot types are available, coming from the bayesplot package. In general, for bayesplot functions that begin with mcmc_, the corresponding plot.type is the remainder of the function name without the leading mcmc_. Examples of many of these plots can be found in this bayesplot vignette.

### Customization

Users may wish to customize some aspects of the resulting plots. For this, the plot() function will output a ggplot object. This makes it possible to modify the plot as if it were any other ggplot object, which allows for many possibilities. One starting point for exploring ggplot2 is here.

p <- plot(fit, pars = 1:4, plot.type = "trace", showplot = FALSE)

p + facet_text(size=15) + legend_none()

Alternatively, users may wish to create a plot that is entirely different from what is available via plot(). This can be facilitated by extracting the posterior samples or the Stan model, via blavInspect():

## list of draws
## (one list entry per chain):
draws <- blavInspect(fit, "mcmc")

## convert the list to a matrix
## (each row is a sample,
##  each column is a parameter)
draws <- do.call("rbind", draws)

## Stan (or JAGS) model
modobj <- blavInspect(fit, "mcobj")

### References

Gabry, Jonah, and Tristan Mahr. 2021. “Bayesplot: Plotting for Bayesian Models.” https://mc-stan.org/bayesplot/.