Identify the product term(s), if any, along a path in a model and return the term(s), with the variables involved and the coefficient(s) of the term(s).

## Arguments

- x
Character. Variable name.

- y
Character. Variable name.

- operator
Character. The string used to indicate a product term. Default is

`":"`

, used in both`lm()`

and`lavaan::sem()`

for observed variables.- fit
The fit object. Currently only supports a lavaan::lavaan object. It can also be a

`lavaan.mi`

object returned by`semTools::runMI()`

or its wrapper, such as`semTools::sem.mi()`

.- est
The output of

`lavaan::parameterEstimates()`

. If`NULL`

, the default, it will be generated from`fit`

. If supplied,`fit`

will ge ignored.- data
Data frame (optional). If supplied, it will be used to identify the product terms.

- expand
Whether products of more than two terms will be searched.

`FALSE`

by default.

## Value

If at least one product term is found, it returns a list with these elements:

`prod`

: The names of the product terms found.`b`

: The coefficients of these product terms.`w`

: The variable, other than`x`

, in each product term.`x`

: The`x`

-variable, that is, where the path starts.`y`

: The`y`

-variable, that is, where the path ends.

It returns `NA`

if no product term
is found along the path.

## Details

This function is used
by several functions in `manymome`

to identify product terms along
a path. If possible, this is done
by numerically checking whether a
column in a dataset is the product
of two other columns. If not possible
(e.g., the "product term" is the
"product" of two latent variables,
formed by the products of indicators),
then it requires the user to specify
an operator.

The detailed workflow of this function can be found in the article https://sfcheung.github.io/manymome/articles/get_prod.html

This function is not intended to be used by users. It is exported such that advanced users or developers can use it.

## Examples

```
dat <- modmed_x1m3w4y1
library(lavaan)
mod <-
"
m1 ~ x + w1 + x:w1
m2 ~ m1 + w2 + m1:w2
m3 ~ m2
y ~ m3 + w4 + m3:w4 + x + w3 + x:w3 + x:w4
"
fit <- sem(model = mod,
data = dat,
meanstructure = TRUE,
fixed.x = FALSE)
# One product term
get_prod(x = "x", y = "m1", fit = fit)
#> $prod
#> [1] "x:w1"
#>
#> $b
#> x:w1
#> 0.2337967
#>
#> $w
#> [1] "w1"
#>
#> $x
#> [1] "x"
#>
#> $y
#> [1] "m1"
#>
# Two product terms
get_prod(x = "x", y = "y", fit = fit)
#> $prod
#> [1] "x:w3" "x:w4"
#>
#> $b
#> x:w3 x:w4
#> 0.5576550 -0.4167135
#>
#> $w
#> [1] "w3" "w4"
#>
#> $x
#> [1] "x"
#>
#> $y
#> [1] "y"
#>
# No product term
get_prod(x = "m2", y = "m3", fit = fit)
#> [1] NA
```