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Parameter Variance/Covariance

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No user picture. IanCero Joined: 02/09/2012
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Confirmatory Factor Analysis and Measurement Models
In LISREL, it is possible to get a matrix of parameter variances and covariances. I need values from this matrix to compute some reliability estimates and am wondering if there is a way to get them from OpenMx. Is this matrix already computed? Is there a good way to access it? I'd appreciate any help!

Replied on Mon, 02/13/2012 - 11:51
Picture of user. Ryne Joined: 07/31/2009

The parameter variance/covariance matrix is the inverse of the Hessian, or matrix of second derivatives of the likelihood function. We provide this matrix in the output under the name calculatedHessian. If your optimized model is named "results", then you can get the parameter covariance matrix like so:


solve(results@output$calculatedHessian)

To be clear, what you're doing is inverting the hessian, which is found in the output slot of 'results' under the heading 'calculatedHessian'.

ryne

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Replied on Mon, 02/13/2012 - 12:06
No user picture. IanCero Joined: 02/09/2012

Thanks for the quick response. I'm really hoping to do everything for my thesis in OpenMx (go open source!) and, as far as I am aware, that was the last thing that I needed.

I wont have a chance to try this until I get home today, but I'm excited.

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