plot_boot: Diagnostic Plots of Bootstrap Estimates in 'lavaan'

Description

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"
)

Value

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

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".

Author

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

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. tools:::Rd_expr_doi("10.1177/2515245920911881")

Examples

Run this code


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)

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