OpenSEM Forums

Include covariates in multivariate cholesky model
Hi,
I have a dataset of twins on 4 time-points and a covariate which does not vary over time. I can fit the Multivariate cholesky decompositon model with ACE components but stuck at the case where I want to include that covariate at each time-point.
This how I was including the covariate (snp),
defSNP <- mxMatrix( type="Full", nrow=1, ncol=2, free=FALSE, labels=c("data.snp1","data.snp2"), name="snp" ) {note that snp1 corresponds to twin 1 and snp2 corresponds to twin 2)

Constraining results of an algebra
Hi!
I am trying to constrain the results of an algebra, either to a fixed value or constraining the results of two algebras to be equivalent. I am using https://openmx.ssri.psu.edu//wiki/mxConstraint-help as a starting point.
Example output is attached, but the relevant lines of code are below
I want to fix AlCO[2,2] to 0 in the first example.
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Combined multi-group and multi-level SEM
I'd like to test whether the variation in the average responses given by participants(the so-called "random intercept" in multilevel model terminology) is different across levels of a specific grouping variable. This seems like something I should be able to do in OpenMx, but I can't figure out how. Specifically, I'm stumped on how to combine multi-group SEM with multi-level SEM, even though I know OpenMx can do each of these separately.
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Moderation doubt
Hi everyone,
I am trying to test if there is a difference in one variable (quantitative) due to another variable (binary but different for each twin).
These variables are related and I want to test if there are different “subtypes” of that disorder (quantitative variable) depending on the value of the other variable (binary variable).
I was thinking to do a moderation analysis (as Rob suggested me in a previous post) as follows:
1-Quantitate variable
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A proper way to handle improper solutions of LGC
Hi all,
I am conducting simulation studies of LGC, and I found that the improper solution rates were pretty high in my model (If a solution with any variance of growth factor less than 0 or any correlation out of [-1, 1], I defined it as improper. Attached is the number of improper solutions out of 1000 replications). I am wondering when specifying an LGC in OpenMx, should I add constraints on variance or correlations? Or I can just exclude those improper solutions from simulation studies simply?
Thanks in advance!

Can OpenMx plot predicted y hat of LGC automatically?
Hi all,
I am conducting latent basis models and have got estimations. I want to plot the functional form of individuals. Is there any way for OpenMx to plot those y hat's for each individual automatically? Or at least can I have those y hat values directly?
Thank you in advance!

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A series of one-day quantitative methods training courses to be held in Autumn/Winter 2018/2019,
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Can OpenMx fit Factor Mixture Models (FMM)?
Dear Users and Maintainers,
Have you used OpenMx to fit Factor Mixture Models (FMM)? I saw that feature in Mplus but I couldn't figure out whether OpenMx can do it or not. Hence the question. Guidance on how to fit FMM using OpenMx would be much appreciated.
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Equality constraints in saturated model
What is the better way to introduce the constrains given that the constrained elements are computed, not defined as matrices?
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Diagnostics for Confidence Intervals
I am estimating a linear latent growth model using two twin samples and I am also estimating a common pathway model in the same samples. The latent slope and intercept are free to correlate with each other and with the latent factor from the common path model. I am trying to compute confidence intervals using mxCI and I am getting errors. When I use the verbose summary, I get the diagnostic and status code of "alpha level not reached iteration limit/blue" on many of my estimates. I've looked around at some documentation/other forum posts.
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