Diagnostic Plots of Bootstrap Estimates in 'lavaan'

Plots for examining the distribution of bootstrap estimates in a model fitted by lavaan.

Usage

plot_boot(
  object,
  param,
  standardized = NULL,
  nclass = NULL,
  hist_color = "lightgrey",
  hist_linewidth = 1,
  density_line_type = "solid",
  density_line_color = "blue",
  density_line_linewidth = 2,
  est_line_type = "dotted",
  est_line_color = "red",
  est_line_linewidth = 2,
  qq_dot_size = 2,
  qq_dot_color = "black",
  qq_dot_pch = 16,
  qq_line_linewidth = 2,
  qq_line_color = "black",
  qq_line_linetype = "solid"
)

Arguments

object: A lavaan::lavaan object with bootstrap estimates stored. For standardized solution and user-defined parameters, the estimates need to be stored by store_boot_est_std() or store_boot_def().
param: String. The name of the parameter to be plotted, which should be the name as appeared in a call to coef().
standardized: Logical. Whether the estimates from the standardized solution are to be plotted. Default is NULL. This is a required parameter and users need to explicitly set it to TRUE or FALSE.
nclass: The number of breaks. This argument will be passed to hist(). Default is NULL.
hist_color: String. The color of the bars in the histogram. It will be passed to hist() for the argument col. Default is "lightgrey".
hist_linewidth: The width of the borders of the bars in the histogram. Default is 1.
density_line_type: String. The type of the line of the density curve in the histogram. It will be passed to lines() for the argument lty. Default is "solid".
density_line_color: String. The color of the density curve in the histogram. It will be passed to lines() for the argument col. Default is "blue".
density_line_linewidth: The width of the density curve in the histogram. It will be passed to lines() for the argument lwd. Default is 2.
est_line_type: String. The type of the vertical line in the histogram showing the point estimate of the parameter. It will be passed to abline() for the argument lty. Default is "dotted",
est_line_color: String. The color of the vertical line showing the point estimate in the histogram. It will be passed to abline() for the argument col. Default is "red".
est_line_linewidth: The width of the vertical line showing the point estimate in the histogram. It will be passed to hist() for the argument lwd. Default is 2.
qq_dot_size: The size of the points in the normal QQ-plot. It will be passed to qqnorm() for the argument cex. Default is 2.
qq_dot_color: String. The color of the points in the normal QQ-plot. It will be passed to qqnorm() for the argument col. Default is "black".
qq_dot_pch: Numeric. The shape of the points in the normal QQ-plot. It will be passed to qqnorm() for the argument pch. Default is 16.
qq_line_linewidth: The width of the diagonal line to be drawn in the normal QQ-plot. It will be passed to qqline() for the argument lwd. Default is 2.
qq_line_color: String. The color of the diagonal line to be drawn in the normal QQ-plot. It will be passed to qqline() for the argument col. Default is "black".
qq_line_linetype: The type of the diagonal line to be drawn in the normal QQ-plot. Default is "solid".

Value

Return the original lavaan::lavaan object invisibly. Called for its side-effect (plotting the graphs).

Details

Rousselet, Pernet, and Wilcox (2021) argued that when using bootstrapping, it is necessary to examine the distribution of bootstrap estimates. This can be done when boot::boot() is used because it has a plot method for its output. This cannot be easily done in model fitted by lavaan::lavaan().

The function plot_boot() is used for plotting the distribution of bootstrap estimates for a model fitted by lavaan in a format similar to that of the output of boot::boot(), with a histogram on the left and a normal QQ-plot on the right.

For free parameters in a model (unstandardized), it can be called directly on the output of lavaan and retrieves the stored estimates.

For estimates of user-defined parameters, call store_boot_def() first to compute and store the bootstrap estimates first.

For estimates in standardized solution, for both free and user-defined parameters, call store_boot_est_std() first to compute and store the bootstrap estimates in the standardized solution.

References

Rousselet, G. A., Pernet, C. R., & Wilcox, R. R. (2021). The percentile bootstrap: A primer with step-by-step instructions in R. Advances in Methods and Practices in Psychological Science, 4(1), 1--10. doi:10.1177/2515245920911881

Author

Shu Fai Cheung https://orcid.org/0000-0002-9871-9448

Examples


library(lavaan)

data(simple_mediation)
mod <-
"
m ~ a * x
y ~ b * m + x
ab := a * b
"
fit <- sem(mod, simple_mediation,
           se = "bootstrap",
           bootstrap = 50,
           iseed = 985714)

# Can plot bootstrap estimates for
# free parameters directly
# Note that 'standardized' must be always be set to
# either TRUE or FALSE. No default value.
plot_boot(fit, "a", standardized = FALSE)


# For estimates of user-defined parameters,
# call store_boot_def() first.
fit <- store_boot_def(fit)
plot_boot(fit, "ab", standardized = FALSE)


# For estimates in standardized solution,
# call store_boot_est_std() first.
fit <- store_boot_est_std(fit)
plot_boot(fit, "a", standardized = TRUE)

plot_boot(fit, "ab", standardized = TRUE)