I'm trying to do a CFA for simulated data. This data has two latent variables with three indicators each, whereas each indicator has a factor loading of 1.
My model looks like this:
"f1 =~ v1 + v2 + v3
f2 =~ v4 + v5 + v6
f2 ~ f1"
In certain cases, all indicators for f1 and/or f2 are generated without error. Unfortunately, lavaan gives the following error when trying to run a CFA:
sample covariance matrix is not positive-definite
When I fix the residual variance of all indicators of f1 and/or f2, I get another error message:
initial model-implied matrix (Sigma) is not positive definite;
check your model and/or starting parameters.
Is lavaan simply not able to deal with data that comes without measurement error?