twostep {modsem} | R Documentation |
Estimate interaction effects in structural equation models (SEMs) using a twostep procedure
Description
Estimate an interaction model using a twostep procedure. For the PI approaches, the lavaan::sam
function
is used to optimize the models, instead of lavaan::sem
. Note that the product indicators are still used,
and not the newly developed SAM approach to estimate latent interactions. For the DA approaches (LMS and QML)
the measurement model is estimated using a CFA (lavaan::cfa
). The structural model is estimated using
modsem_da
, where the estimates in the measurement model are fixed, based on the CFA estimates.
Note that standard errors are uncorrected (i.e., naive), and do not account for the uncertainty in the CFA estimates.
NOTE, this is an experimental feature!
Usage
twostep(model.syntax, data, method = "lms", ...)
Arguments
model.syntax |
|
data |
dataframe |
method |
method to use:
|
... |
arguments passed to other functions depending on the method (see |
Value
modsem
object with class modsem_pi
or modsem_da
.
Examples
library(modsem)
m1 <- '
# Outer Model
X =~ x1 + x2 +x3
Y =~ y1 + y2 + y3
Z =~ z1 + z2 + z3
# Inner model
Y ~ X + Z + X:Z
'
est_dblcent <- twostep(m1, oneInt, method = "dblcent")
summary(est_dblcent)
## Not run:
est_lms <- twostep(m1, oneInt, method = "lms")
summary(est_lms)
est_qml <- twostep(m1, oneInt, method = "qml")
summary(est_qml)
## End(Not run)
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)
# Causal Relationsships
INT ~ ATT + SN + PBC
BEH ~ INT + PBC
BEH ~ INT:PBC
"
uk_dblcent <- twostep(tpb_uk, TPB_UK, method = "dblcent")
summary(uk_dblcent)
## Not run:
uk_qml <- twostep(tpb_uk, TPB_UK, method = "qml")
uk_lms <- twostep(tpb_uk, TPB_UK, method = "lms", nodes = 32, adaptive.quad = TRUE)
summary(uk_lms)
## End(Not run)