setup_ci_plot: Set up information for a dot plot with confidence intervals

Description

Extract the relevant information for a dot plot with confidence intervals of selected effects from (robust) mediation analysis.

Usage

setup_ci_plot(object, ...)
# S3 method for boot_test_mediation
setup_ci_plot(object, parm = NULL,
  type = c("boot", "data"), ...)
# S3 method for sobel_test_mediation
setup_ci_plot(object, parm = NULL,
  level = 0.95, ...)
# S3 method for list
setup_ci_plot(object, ...)

Arguments

object

an object inheriting from class "test_mediation" containing results from (robust) mediation analysis, or a list of such objects.

…

additional arguments to be passed down.

parm

a character string specifying the effects to be included in the plot. The default is to include the direct and the indirect effect(s).

type

a character string specifying which point estiamates and confidence intervals to plot: those based on the bootstrap distribution ("boot"; the default), or those based on the original data ("data"). If "boot", the confidence intervals of effects other than the indirect effect(s) are computed using a normal approximation (i.e., assuming a normal distribution of the corresponding effect with the standard deviation computed from the bootstrap replicates). If "data", the confidence intervals of effects other than the indirect effect(s) are computed via statistical theory based on the original data (e.g., based on a t-distribution the coefficients are estimated via regression). Note that this is only relevant for mediation analysis via a bootstrap test, where the confidence interval of the indirect effect is always computed via a percentile-based method due to the asymmetry of its distribution.

level

numeric; the confidence level of the confidence intervals from Sobel's test. The default is to include 95% confidence intervals. Note that this is not used for bootstrap tests, as those require to specify the confidence level already in test_mediation().

Value

An object of class "setup_ci_plot" with the following components:

a data frame consisting of column Effect indicating the different effects, column Estimate containing the point estimates, column Lower for the lower confidence limit, and column Upper for the upper confidence limit. If a list of "test_mediation" objects has been supplied, there is also a column Method, which takes the names or indices of the list elements to indicate the different methods.

level

numeric; the confidence level used for the confidence intervals of the indirect effect(s).

have_methods

a logical indicating whether a list of "test_mediation" objects has been supplied. If TRUE, the data frame in the ci component contains a column Method.

Details

This function is used internally by ci_plot(). It may also be useful for users who want to produce a similar plot, but who want more control over what information to display or how to display that information.

Examples

Run this code

# NOT RUN {
data("BSG2014")

# run fast and robust bootstrap test
robust_boot <- test_mediation(BSG2014,
                              x = "ValueDiversity",
                              y = "TeamCommitment",
                              m = "TaskConflict",
                              robust = TRUE)

# set up information for plot
setup <- setup_ci_plot(robust_boot, parm = "ab")

# plot only density and confidence interval
ggplot() +
  geom_hline(yintercept = 0, color = "darkgrey") +
  geom_pointrange(aes(x = "Robust bootstrap", y = Estimate,
                      ymin = Lower, ymax = Upper),
                  data = setup$ci) +
  labs(x = NULL, y = "Indirect effect")

# }