# Total Indirect Effect Between Two Variables

Source:`R/total_indirect_effect_list.R`

`total_indirect_effect.Rd`

Compute the total
indirect effect between two
variables in the paths estimated by
`many_indirect_effects()`

.

## Arguments

- object
The output of

`many_indirect_effects()`

, or a list of`indirect`

-class objects.- x
Character. The name of the

`x`

variable. All paths start from`x`

will be included.- y
Character. The name of the

`y`

variable. All paths end at`y`

will be included.

## Details

It extracts the
`indirect`

-class objects
of relevant paths and then add
the indirect effects together
using the `+`

operator.

## 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, control variables excluded
paths <- all_indirect_paths(fit,
exclude = c("c1", "c2"))
paths
#> Call:
#> all_indirect_paths(fit = fit, exclude = c("c1", "c2"))
#> Path(s):
#> path
#> 1 m11 -> m12 -> y
#> 2 x -> m11 -> m12
#> 3 x -> m11 -> m12 -> y
#> 4 x -> m11 -> y
#> 5 x -> m12 -> y
#> 6 x -> m2 -> y
# Indirect effect estimates
out <- many_indirect_effects(paths,
fit = fit)
out
#>
#> == Indirect Effect(s) ==
#> ind
#> m11 -> m12 -> y 0.241
#> x -> m11 -> m12 0.372
#> x -> m11 -> m12 -> y 0.193
#> x -> m11 -> y 0.163
#> x -> m12 -> y 0.059
#> x -> m2 -> y 0.364
#>
#> - The 'ind' column shows the indirect effects.
#>
# Total indirect effect from x to y
total_indirect_effect(out,
x = "x",
y = "y")
#>
#> == Indirect Effect ==
#>
#> Path: x -> m11 -> m12 -> y
#> Path: x -> m11 -> y
#> Path: x -> m12 -> y
#> Path: x -> m2 -> y
#> Function of Effects: 0.780
#>
#> Computation of the Function of Effects:
#> (((x->m11->m12->y)
#> +(x->m11->y))
#> +(x->m12->y))
#> +(x->m2->y)
#>
```