General SEM Discussions

Hello,

Does the scale of a latent variable matter in interpreting results? For instance, I am trying to make a latent variable for cost, but none of my observed variables are in dollars (or any monetary value). If the first indicator loading is fixed to 1, but that is measuring # of cars, how would that affect the other indicators, which are measurements of completely different things (but things that would affect this idea of cost)?

Thanks for any help

Hi All,

I am using OpenMx in conjunction with SEM Trees. As a result of this, I have to include the whole dataset (30,000 x 1200). Right now, it takes about 30 seconds to run the current code:

hpc20 <- mxModel("1 Variable",type="RAM",
mxData(observed=pt_run1,type="raw"),
manifestVars="A_AbsRea",
mxPath(
from= "A_AbsRea" ,
arrows=2,free=T,values=9,labels= "e1"),
mxPath(
from="one",
to="A_AbsRea",

hallo,
I want to ask about optimalization my SEM model. i confused how to set a starting value for each variable? i send my code but in result, i get still NaN in the standar estimation.
in my result, RMSEA still more than 0.08 and the CFI still less than 0.9. so, what should i do?

Hi.
We are planning to do some moderation model analysis on the new data (which we do not have yet) and need to do power analysis before. Is there any script written for OpenMx how to do it? I found some scripts for calssical Mx, but I am not sure I am able to adjust it to moderation models and even if, the output seems to be not compatible with 64-bit Windows.
I would appreciate any help for simulating data driven by such models and for calculating the power.
Thank you beforehand!
Julia

Hello -

I wanted to check with the community if anyone has experience in using SEM for predictive modeling. If yes, how does one approach it. Thanks in advance for your help!

I want to ask what exactly the purpose of setting the starting value in mxPath codes? And what the basic can we use to set it? Is it like trial and error? I set some values but it always generate the NaN value in standard error, so what should I do then? Thank you.

I want to ask you.
actually, I have a problem with my data. My new data is incomplete (missing data). I read on the web if no data is lost then using FIML function, but I am confused what to put where and what. I have tried but I always fail. please help me.
other than that, is there any basis we determine the value? I tried to try to change the value of 0.25-1 and outcome affect the output Standard error of estimate.
thank you.

Hi,
I have 50 binary variables with values of either 0 or 1. I tried to treat these variables as ordinal and fit a growth curve model.
OpenMx gave wrong message:

Running Linear Growth Curve Model
Error: The data object 'Linear Growth Curve Model.data' contains 50 ordered factors but our ordinal integration implementation has a limit of 20 ordered factors.

Is that true that I only can fit 20 ordered factors using OpenMx? Could you point me a direction how to fix this problem? Any help or suggestions will be appreciated. Thanks!

Hi, everyone! I am a rookie of SEM.
To use SEM, I have read some textbooks about it. And there are something I cannot quite sure about.

It is usual that a latent variable has several indicators, let's say three as an example.
[indicator1] <-- (latent variable)
[indicator2] <--
[indicator3] <--

the path diagram above can be represented by equations as follow:

indicator1 = a1 * latent variable + error1 ... (*)
indicator2 = a2 * latent variable + error2 ... (**)
indicator3 = a3 * latent variable + error3 ... (***)

Suppose I have two endogenous variables (A and B) and I draw an arrow (double-headed) between them. What is openmx doing in the background? Is it fitting a correlation between the residuals of A and B?