I try to fit a model of BIS-11 using WLSMV estimator.
model = '
attentional =~ bis5+bis9+bis11+bis20+bis28+bis6+bis24+bis26
motor =~ bis2+bis3+bis4+bis17+bis19+bis22+bis25+bis16+bis21+bis23+bis30
nonplaning =~ bis1+bis7+bis8+bis12+bis13+bis14+bis10+bis15+bis18+bis27+bis29
fit = cfa(model, data = BIS_data, estimator = "WLSMV")
The fit function results in a warning:
In lav_model_estimate(lavmodel = lavmodel, lavpartable = lavpartable, :
lavaan WARNING: the optimizer (NLMINB) claimed the model converged,
but not all elements of the gradient are (near) zero;
the optimizer may not have found a local solution
use check.gradient = FALSE to skip this check.
When I use the summary function i get another warning
In .local(object, ...) :
lavaan WARNING: fit measures not available if model did not converge
and the information that
lavaan 0.6-5 did NOT end normally after 129 iterations"
It doesn't converge with any estimator based on DWLS, however it converges with ML estimators.
What's the reason for this? It's important for me to use the WLSMV.
Thanks in advance,