OpenMx Help

Hello.

Hello.

I read that 64-bit version of OpenMx is under development. Do you have any time frame when approximately it will be available? I am just running an analysis that take a LOT of time since 32-bit R uses only 4 GB of RAM.
Is there an advantage of installing OpenMx on a 64-bit Windows machine even though using 32-bit OpenMx?

Thank you beforehand.
Julia

Hi,

I've added a way to specify and fit LISREL models in OpenMx. The function is called mxLISRELObjective and it operates very similarly to the mxRAMObjective function. Currently, only matrix specification of LISREL models is possible, but I'm working on path specification.

I'm trying to run a CFA model, and I'm receiving some status 6 (code red) errors that I suspect may be due to starting values. I have constrained variances to be positive and have moved the starting values around, but no success.

Two things: 1) do you have any recommendations on how to determine starting values for latent variances, residual variances, covariances, factor loadings, means, etc.? 2) Do you know where I could read more about guidelines for determining starting values?

Thanks!

hi all,
running a simple model f1->{a,b,c} where a & b are ordinal.

runs fine with cov data, or as a raw model, treating the ordinal variables as continuous.

But going to raw with a thresholds matrix and means, it returns the following error.

> m1 = mxRun(m1);
Running m1
Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, :
BLAS/LAPACK routine 'DSYMV ' gave error code -5

Hi,
I just upgraded to the newest version of OpenMx and R 2.15.0. I ran a simple univariate script and everything worked fine until the AE model. This is the error I get when I run the univAEFit:

> univAEFit <- mxRun(univAEModel, intervals=T)
Running univAE
Error: Unknown reference to 'AE.VarComp' detected in a confidence interval specification in model 'univAE' in runHelper(model, frontendStart, intervals, silent, suppressWarnings, unsafe, checkpoint, useSocket, onlyFrontend, useOptimizer).

I was wondering if anyone had some insight on which measure of model fit is the most appropriate (in reference mostly to the 5 different AIC and BIC values output by OpenMX) - both in general situations and in my particular situation. This is most important to us since in our models they aren't agreeing on an answer.

For my particular problem, we're looking at 8 variables (in a twin modeling framework, but we're looking at non-twin models as well) and these variables are split into 4 closely correlated pairs (correlations around .5) that are loosely correlated with one another.

I know there's another similar active thread, but I didn't want to highjack it. Most of the threads I've seen in regards to this error message have some reference to an iteration or line - mine does not. What's in the subject is the entire error.

Hi,
getting this error, which is not very informative as to its source: The problem is a mis-use of rnorm which passes in an numeric(0), i.e. empty array.

Would be nice if we could say "Error in path from "Read7N": Empty list passed in for values : values must contain at least one number)"

Error in allvalues[[i%%length(allvalues) + 1]] : subscript out of bounds

Any clues as to how it could be made more diagnostic?

FYI: This is the path model generating it


test <- mxModel("TEST", type="RAM",
manifestVars = manifests,