manymome (version 0.2.7)

confint.indirect_list: Confidence Intervals of Indirect Effects in an 'indirect_list' Object

Description

Return the confidence intervals of the indirect effects stored in the output of many_indirect_effects().

Usage

# S3 method for indirect_list
confint(object, parm = NULL, level = 0.95, ...)

Value

A two-column data frame. The columns are the limits of the confidence intervals.

Arguments

object

The output of many_indirect_effects().

parm

Ignored for now.

level

The level of confidence, default is .95, returning the 95% confidence interval.

...

Additional arguments. Ignored by the function.

Details

It extracts and returns the stored confidence interval if available.

The type of confidence intervals depends on the call used to compute the effects. This function merely retrieves the stored estimates, which could be generated by nonparametric bootstrapping, Monte Carlo simulation, or other methods to be supported in the future, and uses them to form the percentile confidence interval.

See Also

many_indirect_effects()

Examples

library(lavaan)
data(data_serial_parallel)
mod <-
"
m11 ~ x + c1 + c2
m12 ~ m11 + x + c1 + c2
m2 ~ x + c1 + c2
y ~ m12 + m2 + m11 + x + c1 + c2
"
fit <- sem(mod, data_serial_parallel,
           fixed.x = FALSE)
# All indirect paths from x to y
paths <- all_indirect_paths(fit,
                           x = "x",
                           y = "y")
paths
# Indirect effect estimates
# R should be 2000 or even 5000 in real research
# parallel should be used in real research.
fit_boot <- do_boot(fit, R = 45, seed = 8974,
                    parallel = FALSE,
                    progress = FALSE)
out <- many_indirect_effects(paths,
                             fit = fit,
                             boot_ci = TRUE,
                             boot_out = fit_boot)
out
confint(out)