OpenMx Structural Equation Modeling

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No user picture. Niels Joined: 04/05/2010
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No user picture. StavrosUt Joined: 04/22/2010

Degrees of freedom with raw data

Hello everybody,
I am an amateur in OpenMx. I am trying, for a start, to fit a one-factor model with OpenMx. I am willing to use the path version.
I use type=RAM, and mxData(...type="raw")

I have 1064 observations and 8 items.

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No user picture. bwainscott Joined: 04/02/2010

Newbie Question

Hello, I ran across your website by searching for open source SEM tools. My name is Robert Wainscott and I am an active duty naval officer and PhD student. My institution requires the purchase of PASW Grad Pack (formerly known as SPSS) with Amos 18 included for the SEM piece. I have no idea what SEM is, but I am sure I will find out in the near future. I am comfotable with R as long as I am using Rkward or RCmdr. Me and scripts/CLI are a bit shaky. The questions I pose are: as a Linux/Open Source user:

Can OpenMX be used as a substitute for Amos?

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No user picture. rlucas Joined: 11/17/2009

Question about fitting saturated models with FIML

From other posts on this forum, I mostly understand why fit indexes are not calculated when using FIML. It sounds like the solution is to fit a saturated model and then use this to calculate these indexes. However, when I do this, the saturated model takes an extremely long time to run, and I am wondering (a) whether I am doing something wrong and (b) if there is any way around this.

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No user picture. joecool250 Joined: 02/04/2010

path diagram

when i run the command omxGraphvizm, can i have it load the estimates of the paths as well as the paths themselves??

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No user picture. mtranmer Joined: 01/24/2010

Advice, please, for two factor model setup

Hello,

I am delighted that OpenMx is now available for SEM and I am working my way through the tutorials. However, one of my students has a slightly different two factor model setup to that shown in the tutorial and i am trying to modify the 2 factor example accordingly, but I am getting a bit stuck with the setup ...

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Picture of user. carey Joined: 10/19/2009

mxPath problem

This is from BivariateSaturated_PathCov.R in the documentation

> bivSatModel1 <- mxModel("bivSat1",
+ manifestVars= selVars,
+ mxPath(
+ from=c("X", "Y"),
+ arrows=2,
+ free=T,
+ values=1,
+ lbound=.01,
+ labels=c("varX","varY")
+ ))
Error: The model type of model 'bivSat1' does not recognize paths.

any help?
greg

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No user picture. Matifou Joined: 12/08/2009

Summary of sem: can I remove the summary of variables?

Hi

I'm using openMx in a sweave file, where I show the output of a sem model. I wonder if it is possible to show only the bottom of what is printed by summary, i.e., only the coefficients table and the index, not the individual summary, whihc is pretty long?

Is this possible?

As second question: how do I see the code for summary? I'm not quite comfortable with S4 modelling, in S3 I would have done:
getAnywhere(summary.MxRAMModel)

How do I do with S4?

Thanks a lot!

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No user picture. Matifou Joined: 12/08/2009

Comparing sem() and mxRun() output

Hi

Are the algorithms different in the sem package and OpenMx package for solving a sem model? Or the starting values? The question is actually whether one is expected to get the same results from the different packages? (as an aside: how can I obtain the value of the evaluated objective function? after runnnig mxRun?)

I'm asking as I tried to replicate example "Wheaton et al. alienation data " (see ?sem), I think I succeeded in having the same model but coef differ slighty or much...

run attached example and compare:
summary(Run)

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Picture of user. neale Joined: 07/31/2009

Power calculations for structural equation models

So a question was on SEMNET the other day, as to whether there were any free SEM packages that do power calculations. In essence, OpenMx does, given a bit of help from the R package pwr. Basically, one would fit the true model to the data, fix one or more parameters to predetermined values (usually to zero) and refit the model. Suppose that the difference in the -2lnL fit functions (as might be obtained from two mxRun commands

sat<-mxRun(saturated)
and
sub <-mxRun(submodel)

then the difference in the fit of these two models would be: