Nothing
## ----include = FALSE----------------------------------------------------------
EVAL_DEFAULT <- FALSE
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
eval = EVAL_DEFAULT
)
## ----setup--------------------------------------------------------------------
# library(modsem)
## -----------------------------------------------------------------------------
# library(modsem)
# m1 <- '
# # Outer Model
# X =~ x1
# X =~ x2 + x3
# Z =~ z1 + z2 + z3
# Y =~ y1 + y2 + y3
#
# # Inner Model
# Y ~ X + Z
# Y ~ X:Z
# '
#
# lms1 <- modsem(m1, oneInt, method = "lms")
# summary(lms1, standardized = TRUE) # Standardized estimates
## -----------------------------------------------------------------------------
# qml1 <- modsem(m1, oneInt, method = "qml")
# summary(qml1)
## -----------------------------------------------------------------------------
# # ATT = Attitude
# # PBC = Perceived Behavioral Control
# # INT = Intention
# # SN = Subjective Norms
# # BEH = Behavior
# tpb <- '
# # Outer Model (Based on Hagger et al., 2007)
# ATT =~ att1 + att2 + att3 + att4 + att5
# SN =~ sn1 + sn2
# PBC =~ pbc1 + pbc2 + pbc3
# INT =~ int1 + int2 + int3
# BEH =~ b1 + b2
#
# # Inner Model (Based on Steinmetz et al., 2011)
# INT ~ ATT + SN + PBC
# BEH ~ INT + PBC
# BEH ~ INT:PBC
# '
#
# lms2 <- modsem(tpb, TPB, method = "lms", nodes = 32)
# summary(lms2)
#
# qml2 <- modsem(tpb, TPB, method = "qml")
# summary(qml2, standardized = TRUE) # Standardized estimates
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