# methods

    library(modsem)

There are a number of approaches for estimating interaction effects in SEM. In modsem(), the method = “method” argument allows you to choose which to use.

- `"ca"` = constrained approach (Algina & Moulder, 2001)
- `"uca"` = unconstrained approach (Marsh, 2004)
- `"rca"` = residual centering approach (Little et al., 2006)
  - default
- `"dblcent"`= double centering approach (Marsh., 2013)
- `"pind"` = basic product indicator approach (not recommended)
- `"lms"` = The Latent Moderated Structural equations approach
  - note: there can not be an interaction between two endogenous variables.
- `"qml"` = The Quasi Maximum Likelihood approach.
  - note: can only be done if you have a single endogenous (dependent) variable.
- `"mplus"`
  - estimates model through Mplus, if it is installed

    m1 <- '
    # Outer Model
    X =~ x1 + x2 + x3
    Y =~ y1 + y2 + y3
    Z =~ z1 + z2 + z3

    # Inner model
    Y ~ X + Z + X:Z
    '

    modsem(m1, data = oneInt, method = "ca")
    modsem(m1, data = oneInt, method = "uca")
    modsem(m1, data = oneInt, method = "rca")
    modsem(m1, data = oneInt, method = "dblcent")
    modsem(m1, data = oneInt, method = "mplus")
    modsem(m1, data = oneInt, method = "lms")
    modsem(m1, data = oneInt, method = "qml")

``