add_rsq: Add R-Squares to Endogenous Variables

In semptools: Customizing Structural Equation Modelling Plots

Add R-Squares to Endogenous Variables

Description

Replace the residual variances of exogenous variables by their R-squares in a qgraph::qgraph object.

Usage

add_rsq(semPaths_plot, object, digits = 2L, rsq_string = "R2=", ests = NULL)

Arguments

semPaths_plot	A qgraph object generated by semPaths, or a similar qgraph object modified by other semptools functions.
object	The object used by semPaths to generate the plot. Use the same argument name used in semPaths to make the meaning of this argument obvious. Currently only object of class lavaan is supported.
digits	Integer indicating number of decimal places for the R-squares. Default is 2L.
rsq_string	The string before the R-squares. Default is "R2=".
ests	A data.frame from the parameterEstimates function, or from other function with these columns:? lhs, op, rhs, and est. The rows with op equal to r2 are used to find the R-squares. Only used when object is not specified.

Details

Modify a qgraph::qgraph object generated by semPaths by setting the labels of the residuals of endogenous variables to their R-squares.

Require either the original object used in the semPaths call, or a data frame with the R-square for each endogenous variable.

Currently supports only plots based on lavaan output.

Value

If the input is a qgraph::qgraph object, the function returns a qgraph based on the original one, with R-squares added. If the input is a list of qgraph objects, the function returns a list of the same length.

Examples

mod_pa <-
  'x1 ~~ x2
   x3 ~  x1 + x2
   x4 ~  x1 + x3
  '
fit_pa <- lavaan::sem(mod_pa, pa_example)
lavaan::parameterEstimates(fit_pa)[ , c("lhs", "op", "rhs",
                                       "est", "pvalue", "se")]
m <- matrix(c("x1",   NA,   NA,
               NA, "x3", "x4",
             "x2",   NA,   NA), byrow = TRUE, 3, 3)
p_pa <- semPlot::semPaths(fit_pa, whatLabels = "est",
                         style = "ram",
                         nCharNodes = 0, nCharEdges = 0,
                         layout = m)
p_pa2 <- add_rsq(p_pa, fit_pa)
plot(p_pa2)

mod_cfa <-
 'f1 =~ x01 + x02 + x03
  f2 =~ x04 + x05 + x06 + x07
  f3 =~ x08 + x09 + x10
  f4 =~ x11 + x12 + x13 + x14
 '
fit_cfa <- lavaan::sem(mod_cfa, cfa_example)
lavaan::parameterEstimates(fit_cfa)[ , c("lhs", "op", "rhs",
                                        "est", "pvalue", "se")]
p_cfa <- semPlot::semPaths(fit_cfa, whatLabels = "est",
                          style = "ram",
                          nCharNodes = 0, nCharEdges = 0)
# Place standard errors on a new line
p_cfa2 <- add_rsq(p_cfa, fit_cfa)
plot(p_cfa2)

mod_sem <-
'f1 =~ x01 + x02 + x03
 f2 =~ x04 + x05 + x06 + x07
 f3 =~ x08 + x09 + x10
 f4 =~ x11 + x12 + x13 + x14
 f3 ~  f1 + f2
 f4 ~  f1 + f3
'

# Can be used with mark_se() and mark_sig()
fit_sem <- lavaan::sem(mod_sem, sem_example)
lavaan::parameterEstimates(fit_sem)[ , c("lhs", "op", "rhs",
                                        "est", "pvalue", "se")]
p_sem <- semPlot::semPaths(fit_sem, whatLabels = "est",
                          style = "ram",
                          nCharNodes = 0, nCharEdges = 0)
# Mark significance, and then add standard errors
p_sem2 <- mark_sig(p_sem, fit_sem)
p_sem3 <- mark_se(p_sem2, fit_sem, sep = "\n")
p_sem4 <- add_rsq(p_sem3, fit_sem)
plot(p_sem4)

semptools documentation built on April 4, 2025, 12:49 a.m.