Mixture Distribution and Latent Class Models

Is there a way to add covariates in growth mixture model
Hi,
I have a script for the 2-class growth mixture model (please see attached). I am wondering if I can add covariate (say x1) as a covariate of my model. I may want to see the effect of x1 on the latent classes only and also of it on both latent classes and the growth factors. As my understanding, in MPlus, the first scenario can be expressed as "c#1 on x1" and the second one can be written as "c#1 on x1" and "int on x1; slp on x1" of each class, but I have zero idea to translate to OpenMx. Any advice would be appreciated.

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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A couple of questions about GMMs
Hi all,
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Carrying out latent profile analysis (LPA) by adapting code examples for a two-factor model and growth mixture models
Hi everyone. I'm new to both OpenMX and mixture models and am trying to do a latent profile analysis, or a mixture model (initially with two classes) of a Two-factor Model.
With the good documentation and code examples for Two-factor Models and mixture models (specifically the code for a growth mixture model), I tried to combine the two. However, when I run it, I get the following error that I'm having trouble debugging:
Error: The reference 'Class1.fitfunction' is unknown in the algebra named 'Latent Profile Model.mixtureObj'

GMM Start Values
I thought I might post this to see if anyone has come across a similar problem. In running a growth mixture model within OpenMx, I have been stymied by status code 10 despite trying mxTryHard (and mxTryHardWideSearch) and moving the starting values around by hand. The strange thing is that this occurs with actual data and with simulated data excluding missingness. Does anyone have a recommendation regarding starting values for a growth mixture model?
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GMM with missing data
Hi all,
I have been working on applying growth mixture model to psychology data with missing data. I know I can use existing software to deal with the missing data. But I want to understand the math behind of it. There is one paper for the Growth mixture model detailing the math titled "Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm". I want to know the methodology of the growth mixture model with missing data. Can anyone show me the math or which paper should I refer to?
Thanks a lot.
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GMM with Concomitant Variable
How would you formulate the growth mixture model to include a concomitant variable (which as I understand it, would allow the prior probabilities to depend on an explanatory variable).
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Nonlinear factors
Hi All,
I am trying to do a factor model with continuous and ordinal data in which the factors are nonlinear, and hence I am approximating their distribution by a mixture of normal distributions. If OpenMx can support it, are there any examples?
Thanks!
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the number of observed statistics in the mixture models
Hi,
I am fitting a mixture model for a genetic association test that includes sibships of variable sizes, with observed and missing genotypes; the model specification is based on the Acemix2.R script.
I would like to know if it is possible to obtain the correct number of observed statistics without being necessary to specify it manually in the summary() function.

Estimation of class transitions
Currently, I am studying three mixed variables in which I expect dissimilar classes for each of the three variables. It is not unlike example 8.2 in the Mplus manual (only with continuous variables). I can do this in Mplus, but I am wondering if it is also possible in OpenMx. So I need to define separate classes for each variable, but the definition of the model is a puzzle to me. Is it possible (yet)? If so, how do I define the matrix of class probabilities and how do I bind the six classes and their objectives together?
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