OpenMx Help

After using omxGraphviz() to output a .Dot plot from my OpenMx model, I get a diagram of the model, but no parameter estimates are overlaid on the diagram. Is there a way to do this? Thanks in advance.

Hi all,

I ran a relatively simple path analytic model with four manifest variables, three causal paths, and one unanalyzed relationship. The model has 2 df. I used the code below but got the following error message:

"In model 'Apgar Model 2' NPSOL returned a non-zero status code 1. The final iterate satisfies the optimality conditions to the accuracy requested, but the sequence of iterates has not yet converged. NPSOL was terminated because no further improvement could be made in the merit function (Mx status GREEN). "

Hello everybody,

Comment from student on getting a helpful error in OpenMX of the form "I'm sorry I can't..."

"Gee: That's the first time I've ever seen R talk in the first person: That's nice!"

:-)

Instead of having users access a blind URL and run a a blind script, i wonder if a one-liner like this might be easier to follow for people?

Suggested new instruction

install.packages('OpenMx', repos='http://openmx.psyc.virginia.edu/testing/')

Current

source("http://openmx.psyc.virginia.edu/getNewOpenMx.R")
# which runs this silently
repos <- c('http://openmx.psyc.virginia.edu/testing/')
install.packages(pkgs=c('OpenMx'), repos=repos)

I'm on a grant whose goal is to develop reliable kinship links to facilitate BG and other developmental studies with the NLSY samples (eg, http://www.bls.gov/nls/nlsy79.htm). We're developing an R package (cran.r-project.org/web/packages/NlsyLinks/) that assists with many of the common manipulations and analyses. We're targeting all BG researchers who are interested in the NLSY, including those with limited experience in R.

OpenMx seems like a natural fit for our examples, but I'm hesitant to use it in our basic documentation, because of two deployment issues:

I'm slowly converting to OpenMX because of its fiml capabilities. I recently built two models that are shown in the enclosed attachments. You will notice that the correlation between T and P is identical in both models (whether S or D is used). However, when I try to replicate these results in OpenMX, I don't get identical results; they're usually about .04 different, which is quite significant for what I'm doing.

Here's my openMX code:

sem.model.S = mxModel("Two Factor Model Path Specification",
type="RAM",
dd,
manifestVars = names(data),
latentVars = c("T", "P"),

I'm sorry if this is a too specific question, I tried to use the Python parser but I am totally unfamiliar with Python and can't get it working.

I keep finding differences between my Mx and OpenMx analysis and I think I must have made a mistake in translating the following algebra:

in Mx:

G = (Y-X)@(A.((A.A)*(V-J))) + X@(A.((U-I)*(A.A)));

in OpenMx (wrong?):

algebraG = mxAlgebra(expression = (Y-X) %x% (A*((A*A)%*%(V-J))) + X %x% (A * ((U-I)%*%(A*A))), name = "G")