Attachment | Size |
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source.R [6] | 2.23 KB |

sample_covariance_matrix.txt [7] | 4.43 KB |

I have conducted a large scale numerical simulation study to see small

sample properties of SEM and then have the following question:

I would appreciate it if you could teach me why MLEs in a CFA model are

different between analyses of raw data and covariance matrix data in

OpenMx package of R. Are the optimization methods employed different?

The maximum difference I encountered is 0.084267.

When I compare the results, I adjusted their scales, i.e., multiplied by

sqrt(N/N-1) for factor loadings and by N/N-1 for error variances.

The adjustment can approach the two estimates to each other closely.

The code and sample covariance matrix are in the attachment.

I would be glad, if someone helped me.