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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")

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They may not be fully stable and should be used with caution. We make no claims about them.