What we need from you involves three components. The first component is the script itself. We can help you remove any locale specific information, such as setwd() or other things. The second component is the data to run the model. If your data is sensitive or unpublished, we have several workarounds. Generating synthetic data that preserves some characteristics of the original data is one option. Generating completely garbage data is sometimes also sufficient as long as the optimizer is performing the same types of behavior. The third component is to add omxCheck...() statements at the end of the script. These statements validate the results of running a model, and they throw an error if validation fails. Here are some examples of omxCheck..() statements:
omxCheckCloseEnough(mxEval(omxAllInt(Cov, Means, Thresh), testAllint1), as.matrix(c(.99, .01)), 0.001) omxCheckIdentical(mxEval(D, model), as.matrix(c(1,2,3))) omxCheckError(mxEval(objective + foo, model, TRUE), 'non-conformable arrays') omxCheckTrue(identical(generated, reference)) omxCheckSetEquals(namespace$entities$model2, c('B', 'data', 'model3'))
So please consider donating your script to our test system. All scripts are released with the Apache Public License 2.0, as is true of all the source code to the OpenMx project. Your contribution helps us all.
Help with donating your models
You can find fakeData on the wiki: http://openmx.psyc.virginia.edu/wiki/generating-simulated-data
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