About the output of lavaan for lisrel model

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asas asas

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Jan 15, 2019, 5:43:43 PM1/15/19
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Dear All,
I have a question about the lavaan package for the general SEM or lisrel model.There is a parameter matrix $Phi$,which makes up the covariance matrix of the exogenuous latent variables and is to be estimated.
Does lavaan check whether the estimated matrix of this $Phi$ is also positive definite?Or the elements of this matrix are estimated freely.
In the file 'lavaan_model_estimate.R',it seems to check the positive definiteness of the initial value of Sigma.However this Sigma may not be the $Phi$, the covariance matrix of the exogenuous latent variable.

Thanks,
Tom

Terrence Jorgensen

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Jan 16, 2019, 6:11:09 PM1/16/19
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There is a parameter matrix $Phi$,which makes up the covariance matrix of the exogenuous latent variables and is to be estimated.

lavaan only uses the "Y side" of the LISREL model.  So there is no Phi, only Psi, which includes (co)variances of all (exogenous and endogenous) latent variables.  

Does lavaan check whether the estimated matrix of this $Phi$ is also positive definite?

Yes, if the the "check.post" option is set to TRUE, it will check that after estimation.

lavOptions("check.post")

In the file 'lavaan_model_estimate.R',it seems to check the positive definiteness of the initial value of Sigma.

Yes, it checks the model-implied Sigma *implied by the starting values" before estimation, if the "check.start" option is set to TRUE.

lavOptions("check.start")

Terrence D. Jorgensen
Assistant Professor, Methods and Statistics
Research Institute for Child Development and Education, the University of Amsterdam


asas asas

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Jan 22, 2019, 4:02:03 PM1/22/19
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Thanks.
A final extra question is that, for those variances of the residuals,does lavaan parameter them in the scale of sigma^2 or sigma?If sigma^2 is parameterized, does lavaan add the constraints that they should be positive?
Best,
Yilun

在 2019年1月16日星期三 UTC-5下午6:11:09,Terrence Jorgensen写道:

Terrence Jorgensen

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Jan 25, 2019, 9:52:31 AM1/25/19
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does lavaan parameter them in the scale of sigma^2

Yes, they are variances, not SDs.
 
If sigma^2 is parameterized, does lavaan add the constraints that they should be positive?

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