OpenMx Developer Forums

Crashing R in OS X
Here's an interesting one...
So I've recently been working on converting an mx script to OpenMx (file attached). I might be doing something I shouldn't, but the script caused R on my Mac to close w/out explanation or warning. Everything goes fine until I hit "mxRun." I ran this under Windows XP and got the following error:
> EstModel <- mxRun(CoupledModel)
Running CoupledModel
Error in mxRun(CoupledModel) :
BLAS/LAPACK routine 'DGEMM ' gave error code -13
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loading packages conditionally
The OpenMx repository has a work-in-progress feature that generates graphs from RAM style models. This package requires the Rgraphviz library. I don't want to add Rgraphviz as a required library. Not all users will need to make graphs, and it turns out that the Rgraphviz library can be a pain to install on Windows (you need a specific version of the Graphviz library that is hidden on their website). So this feature conditionally works if the Rgraphviz package is installed.
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Bootstrapping Confidence Intervals
I couldn't find info on bootstrapping confidence intervals on the site, so I wanted to put in a plug for such an option. Kris Preacher and I were talking about this yesterday.
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UnivariateTwinAnalysis_MatrixRaw.R
There are close to zero comments on this script, and much of it is quite obscure.
1. There are still places with T instead of TRUE and unlabeled parameters relying on being in the right place:
mxMatrix("Full", 1, 2, T, 20, "mean", dimnames=list(NULL, selVars), name="expMeanMZ"),
2. Most matrices need a comment about what it is they are holding, i.e.:
mxMatrix("Full", nrow=1, ncol=1, free=TRUE, values=.6, label="a", name="X") # what is this for?
mxAlgebra(X %*% t(X), name="A"), # what does this do?
Proposing an algebra for the the groups is critical and needs a comment:
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Ordinal Data Proposal (#2)
I've been talking to Ryne about this, and I think we've put together a fairly reasonable proposal for the user experience for ordinal data.
We welcome comments and suggestions.
A) From the pathy perspective:
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mxPath
topic for discussing mxPath() function
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So many AICs, so little time. What's a summary() to do?
There has been an ongoing discussion on both the optimizer forum and the developer's mailing list about which AIC to use. This thread is here to gather the discussion in one place.
Since the major SEM packages differ in the way they calculate AIC, I proposed we print something like:
AIC (Mx) = -123456 AIC (Amos) = 654321 AIC (MPlus) = 234567 AIC (LISREL) = 132435
Let the AIC discussions begin!

using mxModel
questions about mxModel
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hangovers from Mx
There are places in the demo scripts that inherit things from Mx that are not necessary: like the fact that Mx couldn't read files with a labels line..
So in
data(twinData) twinVars <- c('fam','age','zyg','part','wt1','wt2','ht1','ht2','htwt1','htwt2','bmi1','bmi2')
Much easier to say
data(twinData) twinVars = names(twinData) # maybe with a comment so people know what is going on # 'fam','age','zyg','part','wt1','wt2','ht1','ht2','htwt1','htwt2','bmi1','bmi2'
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Underlying model for diagrams: Multiple group etc.
I guess the GUI will have to create a fairly universal underlying script model, allowing it to create the full-spectrum of models.
What underlying script model is the GUI expecting to generate/read? (i.e., should we think about a RAM+ that can handle all models, or pick a suite that covers the bases, expanding as the GUI capability expands?
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