fit {cSEM}R Documentation

Model-implied indicator or construct variance-covariance matrix


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).


  .object    = NULL, 
  .saturated = args_default()$.saturated,
  .type_vcv  = args_default()$.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 Bollen (1989). 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).


Either a (K x K) matrix or a (J x J) matrix depending on the type_vcv.


Bollen KA (1989). Structural Equations with Latent Variables. Wiley-Interscience. ISBN 978-0471011712.

See Also

csem(), foreman(), cSEMResults

[Package cSEM version 0.4.0 Index]