Delta_Med in a 'delta_med'-Class Object

Return the estimate of Delta_Med in a 'delta_med'-class object.

Usage

# S3 method for delta_med
coef(object, ...)

Arguments

object: The output of delta_med().
...: Optional arguments. Ignored.

Value

A scalar: The estimate of Delta_Med.

Details

It just extracts and returns the element delta_med in the output of delta_med(), the estimate of the Delta_Med proposed by Liu, Yuan, and Li (2023), an \(R^2\)-like measure of indirect effect.

References

Liu, H., Yuan, K.-H., & Li, H. (2023). A systematic framework for defining R-squared measures in mediation analysis. Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000571

Author

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

Examples


library(lavaan)
dat <- data_med
mod <-
"
m ~ x
y ~ m + x
"
fit <- sem(mod, dat)
dm <- delta_med(x = "x",
                y = "y",
                m = "m",
                fit = fit)
dm
#> Call:
#> delta_med(x = "x", y = "y", m = "m", fit = fit)
#> 
#> Predictor (x)       : x 
#> Mediator(s) (m)     : m 
#> Outcome variable (y): y 
#> 
#> Delta_med: 0.230
#> 
#> Paths removed:
#>  m~x
print(dm, full = TRUE)
#> Call:
#> delta_med(x = "x", y = "y", m = "m", fit = fit)
#> 
#> Predictor (x)       : x 
#> Mediator(s) (m)     : m 
#> Outcome variable (y): y 
#> 
#> Delta_med: 0.230
#> 
#> Paths removed:
#>  m~x
#> 
#> Additional information:
#> R-sq: Original                            : 0.351
#> R-sq: Mediator(s) removed                 : 0.121
#> Variance of y                             : 6.273
#> Variance of predicted y                   : 2.203
#> Variance of predicted: mediator(s) removed: 0.759
coef(dm)
#> [1] 0.2302121