Calculate the model-implied indicator or construct variance-covariance (VCV) matrix. Currently only the model-implied VCV for recursive linear models is implemented (including models containing second order constructs).
fit(
.object = NULL,
.saturated = args_default()$.saturated,
.type_vcv = args_default()$.type_vcv
)Either a (K x K) matrix or a (J x J) matrix depending on the type_vcv.
An R object of class cSEMResults resulting from a call to csem().
Logical. Should a saturated structural model be used?
Defaults to FALSE.
Character string. Which model-implied correlation matrix should be calculated? One of "indicator" or "construct". Defaults to "indicator".
Notation is taken from Bollen1989;textualcSEM.
If .saturated = TRUE the model-implied variance-covariance matrix is calculated
for a saturated structural model (i.e., the VCV of the constructs is replaced
by their correlation matrix). Hence: V(eta) = WSW' (possibly disattenuated).
csem(), foreman(), cSEMResults