# Extract the Indirect Effect or Conditional Indirect Effect

Source:`R/coef_indirect.R`

`coef.indirect.Rd`

Return the estimate of
the indirect effect in the output of
`indirect_effect()`

or or the
conditional indirect in the output of
`cond_indirect()`

.

## Usage

```
# S3 method for indirect
coef(object, ...)
```

## Arguments

- object
The output of

`indirect_effect()`

or`cond_indirect()`

.- ...
Optional arguments. Ignored by the function.

## Details

It extracts and returns the
element `indirect`

. in an object.

If standardized effect is requested
when calling `indirect_effect()`

or
`cond_indirect()`

, the effect
returned is also standardized.

## Examples

```
library(lavaan)
dat <- modmed_x1m3w4y1
mod <-
"
m1 ~ x + w1 + x:w1
m2 ~ x
y ~ m1 + m2 + x
"
fit <- sem(mod, dat,
meanstructure = TRUE, fixed.x = FALSE,
se = "none", baseline = FALSE)
est <- parameterEstimates(fit)
# Examples for indirect_effect():
# Inidrect effect from x through m2 to y
out1 <- indirect_effect(x = "x", y = "y", m = "m2", fit = fit)
out1
#>
#> == Indirect Effect ==
#>
#> Path: x -> m2 -> y
#> Indirect Effect: 0.052
#>
#> Computation Formula:
#> (b.m2~x)*(b.y~m2)
#> Computation:
#> (0.16554)*(0.31451)
#> Coefficients of Component Paths:
#> Path Coefficient
#> m2~x 0.166
#> y~m2 0.315
#>
coef(out1)
#> y~x
#> 0.05206422
# Conditional Indirect effect from x1 through m1 to y,
# when w1 is 1 SD above mean
hi_w1 <- mean(dat$w1) + sd(dat$w1)
out2 <- cond_indirect(x = "x", y = "y", m = "m1",
wvalues = c(w1 = hi_w1), fit = fit)
out2
#>
#> == Conditional Indirect Effect ==
#>
#> Path: x -> m1 -> y
#> Moderators: w1
#> Conditional Indirect Effect: -0.031
#> When: w1 = 1.228
#>
#> Computation Formula:
#> (b.m1~x + (b.x:w1)*(w1))*(b.y~m1)
#> Computation:
#> ((0.46277) + (0.23380)*(1.22806))*(-0.04197)
#> Coefficients of Component Paths:
#> Path Conditional Effect Original Coefficient
#> m1~x 0.750 0.463
#> y~m1 -0.042 -0.042
#>
coef(out2)
#> y~x
#> -0.03147387
```