OpenMx 2.0 Discussion

If you are posting to report an issue with OpenMx 2.0, we ask that your post include, at minimum, the following:

1. Any relevant error messages, strange output, and so forth, as the case may be.
2. The version of OpenMx you're running.
3. The version of R you're running.
4. Your operating system and architecture (e.g., "x86_64 Linux").
5. OpenMx's default optimizer (which will always be NPSOL for OpenMx versions 1.4 or older).

Note that you can see items #2 thru #5 above by entering mxVersion() at the R prompt.

The following issues are mentioned in the third beta's announcement:

• The Windows binaries of this third beta were compiled without enabling multiple threads (i.e., parallel processing with multiple cores).
• CSOLNP can still crash or freeze up R, or terminate calculation prematurely, when calculating confidence intervals. This behavior appears to be Windows-specific, and almost entirely confined to 64-bit R.
  

Hi everyone,

I am working on a longitudinal project recently and our focus is to estimate a change. We are interested in fitting a quadratic latent change score model. Basically, we are using the code attached as the template, which is from Grimm et al., 2016, Chapter 18, Page 467-469. I was wondering if it is possible to estimate the mean and variance of each "dy" and "ly" (which are latent variables) in the model specification using some OpenMx functions directly? Thank you very much!

Hi everyone,

Hope you are enjoying the winter break!

I am trying to estimate a derived parameter using mxEval() and mxSE(). The function mxEval() works well, but mxSE() reports a warning message as below and produces NA for the standard error.

"1: In mxSE(paste0("instant_rate_est", j), model = model, ... :
Some diagonal elements of the repeated-sampling covariance matrix of the point estimates are less than zero or NA.
I know, right? Set details=TRUE and check the 'Cov' element of this object. "