Nothing
## ----include = FALSE----------------------------------------------------------
EVAL_DEFAULT <- FALSE
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
eval = EVAL_DEFAULT
)
## ----setup--------------------------------------------------------------------
# library(modsem)
## -----------------------------------------------------------------------------
# tpb_uk <- "
# # Outer Model (Based on Hagger et al., 2007)
# ATT =~ att3 + att2 + att1 + att4
# SN =~ sn4 + sn2 + sn3 + sn1
# PBC =~ pbc2 + pbc1 + pbc3 + pbc4
# INT =~ int2 + int1 + int3 + int4
# BEH =~ beh3 + beh2 + beh1 + beh4
#
# # Inner Model (Based on Steinmetz et al., 2011)
# INT ~ ATT + SN + PBC
# BEH ~ INT + PBC
# BEH ~ INT:PBC
# "
#
# fit <- modsem(tpb_uk,
# data = TPB_UK,
# method = "lms",
# nodes = 32, # Number of nodes for numerical integration
# adaptive.quad = TRUE, # Use quasi-adaptive quadrature
# adaptive.frequency = 3, # Update the quasi-adaptive quadrature every third EM-iteration
# algorithm ="EMA", # Use accelerated EM algorithm (Default)
# convergence.abs = 1e-4, # Relative convergence criterion
# convergence.rel = 1e-10, # Relative convergence criterion
# max.iter = 500, # Maximum number of iterations
# max.step = 1) # Maximum number of steps in the maximization step
# summary(fit)
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