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

By *brauer*

Created *03/09/2012 - 18:21*

Fri, 03/09/2012 - 18:21 — brauer [1]

Hi all,

Can I ask you a general question about OpenMx? As a teacher of SEM classes and as a supervisor of graduate students doing research in social psychology I am looking for a R-based SEM package that allows me to generate quite easily (with a relatively simple script) different pieces of information that my colleagues, the reviewers of my manuscripts, and I use to evaluate structural models. The check list that I typically give my students is pasted below. Unless I am mistaken, OpenMx does not allow me to easily obtain the relevant information (except (1), (2), (7), (9) and (12)). If I understand, you (the developers of OpenMx) are mostly interested in advanced features, such as parallel runs, simulations, bootstrap, etc. Does this mean I should use a different package in the future? If yes, do you know of a package that allows me to get the information listed below?

Thanks a million in advance.

-- M

Criteria to evaluate a hypothesized structural model:

1) Is chi-square non-significant?

2) Is RMSEA < .05 ?

3) Is the lower bound of the 90% CI of the RMSEA < .01 ?

4) Is the upper bound of the 90% CI of the RMSEA < .10 ?

5) Is p close non-significant ? [Note: p close tests the null hypothesis that RMSEA in the population is < .05]

6) Is the SRMR < .08 ?

7) Is the CFI > .95 ?

8) Are other classic fit indices satisfactory (GFI, TLI, etc.)?

9) Are all correlation residuals < .10 ?

10) Are all standardized residuals < 1.96 ? [less important in large samples]

11) Does the quantile plot of standardized residuals look OK (do the standardized residuals fall along a diagonal line)?

12) Are the parameter estimates OK: do they make sense? are they significant?

13) Are indirect effects statistically significant? [test with bootstrap method]

14) Do we have sufficient statistical power for the test of the close-fit hypothesis and the test of the not-close-fit hypothesis? [generate script with Preacher's web site]

15) Can we argue against equivalent and near-equivalent models?

Model comparison:

16) Is the difference chi-square significant?

17) Does one of the models have a lower AIC, BIC?

**Links:**

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

[2] http://openmx.psyc.virginia.edu/thread/1283

[3] http://openmx.psyc.virginia.edu/thread/1276

[4] http://openmx.psyc.virginia.edu/forums/openmx-help/openmx-general-help