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. Different approaches can be categorized into two groups: Product Indicator (PI) and Distribution Analytic (DA) approaches.
"ca" = constrained approach (Algina & Moulder, 2001)
"uca" = unconstrained approach (Marsh, 2004)"rca" = residual centering approach (Little et al., 2006)"dblcent" = double centering approach (Marsh., 2013)
"pind" = basic product indicator approach (not recommended)"lms" = The Latent Moderated Structural equations (LMS) approach, see the vignette"qml" = The Quasi Maximum Likelihood (QML) approach, see the vignette"mplus"
m1 <- '
# Outer Model
X =~ x1 + x2 + x3
Y =~ y1 + y2 + y3
Z =~ z1 + z2 + z3
# Inner model
Y ~ X + Z + X:Z
'
# Product Indicator Approaches
modsem(m1, data = oneInt, method = "ca")
modsem(m1, data = oneInt, method = "uca")
modsem(m1, data = oneInt, method = "rca")
modsem(m1, data = oneInt, method = "dblcent")
# Distribution Analytic Approaches
modsem(m1, data = oneInt, method = "mplus")
modsem(m1, data = oneInt, method = "lms")
modsem(m1, data = oneInt, method = "qml")
Need a high-speed mirror for your open-source project?
Contact our mirror admin team at info@clientvps.com.
This archive is provided as a free public service to the community.
Proudly supported by infrastructure from VPSPulse , RxServers , BuyNumber , UnitVPS , OffshoreName and secure payment technology by ArionPay.