OpenMx Structural Equation Modeling
Charlotte
Joined: 07/02/2012
Simplex models with thresholds - CIs?
Dear all,
I have fitted a simplex model with six time points. It's a threshold model with 2 thresholds. I fixed the thresholds and freely estimated the means. I used the CSOLNP optimizer.
I get stable estimates, they are in accordance with what I would expect based on the univariate results, and the gradients look ok.
As a next step, I wanted to calculate confidence intervals, but I only get this:
confidence intervals:
lbound estimate ubound note
atm21 NA 0.4871751 NA !!!
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Jorien
Joined: 02/08/2013
Joint Ordinal-Continuous Model
Hi everyone,
I am trying to run a joint ordinal-continuous model.
In my model I have a continuous variable (varA) and an ordinal variable with 1 threshold (varB).
There are 5 zygosity groups (MZM, DZM, MZF, DZF, DOS) and a covariate age which
I modeled separately for men and women.
The model is actually running perfectly fine (no errors) and the estimates for the thresholds for varB
look good and are what I would have expected.
However, the estimates for the means are all way too low when I compare them with the raw data.
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rabil
Joined: 01/14/2010
Convert RAM Model to LISREL
I need to compute factor scores which only works in OpenMx if the model type is LISREL. I've attached the model code that includes creating a path diagram for the RAM version. The RAM model code works fine in estimating the parameters. When I convert it to "type="LISREL"", I get various error messages.
This shows the specification for the endogenous and exogenous variables in the LISREL version:
manifestVars=list(
endo=c("c_el","c_nc_el","c_or","c_nc_or",
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Lisa M
Joined: 08/19/2013
P value of 1 in mxCompare
Hello,
I am working on an analysis of a univariate sex limitation model for depression and I have run into a potential problem. When comparing the homogeneity ACE model to the AE model, I get a p-value of 1 in mxCompare. The fit of the models are very similar:
> mxCompare(HomACEModelFit,HomAEModelFit)
base comparison ep minus2LL df AIC diffLL diffdf p
1 HomACE
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dadrivr
Joined: 01/19/2010
Constraining loadings on factor so average of loadings equals 1 and average of intercepts equals 0
I am running a CFA and would like to use the "effects coding" method of identification described by Little, Slegers, and Card (2006). In the effects coding method, the loadings of a factor are constrained so that the average of the loadings equals 1 and the average of the intercepts equals 0. How can I do this with OpenMx? I imagine it involves mxConstraint or mxAlgebra, but am not sure where to begin. Here's a small example of a model that I'd like to modify to use effects coding:
oneFactorModel <- mxModel("CFA",
type="RAM",
Charlotte
Joined: 07/02/2012
Charlotte
Joined: 07/02/2012
Simplex model & sex differences
Dear all,
I am working on a simplex script in openMx. There are quantitative and qualitative sex differences for my phenotype, so I estimate separate paths for males and females and I would also like to freely estimate the dos correlations between the latent As. However, I am struggling with the transmission paths.
Probably, someone else has already dealt with this. I would like to know whether there are any simplex scripts available that take into account sex differences?
Regards
Charlotte
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yoosoo
Joined: 06/19/2014
Multilevel SEM with complex sampling
Dear all,
Would you confirm if OpenMx supports multilevel SEM on complex sampling survey data, with categorical outcome? (each datapoint has different weight)
Thank you!
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CharlesD
Joined: 04/30/2013
Returned matrices (expCov, expMean, A,S, etc) only reflect last row of data
Hi folks. I mentioned this to Joshua who asked me to post it here for further input. While wondering about some strange output in one of my functions the other day I discovered that the matrices output by openmx only reflect the last calculated row of data. I believe this only becomes evident when definition variables are used, such that the A S or M matrices (when using RAM format, though I don't believe it's limited to this case) depend on the definition variable.
brandmaier
Joined: 02/04/2010
Standardized estimates under equality constraints
I was wondering how OpenMx treats standardized estimates under equality constraints.
I ran a linear latent growth curve model in OpenMx and constrained all residual variances to be equal. Not surprisingly, they all get to be the same unstandardized estimate. However, OpenMx reports only a single standardized estimate for the residual, which happens to be the one associated with the first observation. Even if the unstandardized estimates are constrained to be equal, the unstandardized ones need not be and in reality seldom are the same.
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