Published on *OpenMx* (http://openmx.psyc.virginia.edu)

By *Ami*

Created *02/22/2012 - 20:37*

Wed, 02/22/2012 - 20:37 — Ami [1]

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.

Attachment | Size |
---|---|

source.R [2] | 2.23 KB |

sample_covariance_matrix.txt [3] | 4.43 KB |

**Links:**

[1] http://openmx.psyc.virginia.edu/users/ami

[2] http://openmx.psyc.virginia.edu/sites/default/files/source.R

[3] http://openmx.psyc.virginia.edu/sites/default/files/sample_covariance_matrix.txt

[4] http://openmx.psyc.virginia.edu/thread/1345

[5] http://openmx.psyc.virginia.edu/thread/78

[6] http://openmx.psyc.virginia.edu/forums/openmx-developer-forums/optimizers