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EVAL_DEFAULT <- FALSE knitr::opts_chunk$set( collapse = TRUE, comment = "#>", eval = EVAL_DEFAULT )
library(modsem)
As of version 1.0.20, the modsem function supports the estimation of models
with composite constructs, when using method="lms". The approach is based
on Tamara Schamberger, Florian Schuberth, Jörg Henseler & Yves Rosseel, 2015.
Depending on your lavaan version (>=0.6-20), composite constructs can also
be used with the product indicator approaches (e.g., method="dblcent").
Here we can see a simple example, using the LMS approach with the TPB dataset.
tpb <- ' # Outer Model (Based on Hagger et al., 2007) # Latent Variables SN =~ sn1 + sn2 PBC =~ pbc1 + pbc2 + pbc3 INT =~ int1 + int2 + int3 # Composites ATT <~ att1 + att2 + att3 + att4 + att5 BEH <~ b1 + b2 # Inner Model (Based on Steinmetz et al., 2011) INT ~ ATT + SN + PBC BEH ~ INT + PBC + INT:PBC ' fit <- modsem(tpb, TPB, method = "lms", nodes = 32) summary(fit)
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