Hi, I've been playing a bit around with SEM models and open-mx and I am having some trouble with derivation of the 'saturated -2 log likelihood' output provided by the summary screen.

Shouldn't the Saturated model be zero always except for some machine error? Instead it tends to be fairly close to a model with 1 degree of freedom.

I might be misunderstanding something but for the saturated model where the Implied model under this condition is equal to the Sample covariance matrix which should yield a discrepancy function of zero.

So, in slightly more explicit terms is this output actually related to the derivation of the -2 * log(Likelihood Ratio) for H_0: Sigma is equal to the Saturated model, where Sigma is the covariance of a multi-variate normal distribution, or is it something else?

Thanks,

Jonathan