Behavioral Genetics Models

Question about covariates/definition variables
I have a question about covariates/definition variables. I have noticed that in most of the scripts (Boulder workshop) covariates are included as definition variables (also in GxE models). I just wondered if covariates could be included as manifest(measured) variables and a regression path with the studied phenotype. I know both methods should be equivalent but this would allow to include missing values. Is there any reason/advantage for including covariates always as definition variables?

Trivariate Cholesky decomposition model
I have a script from SGDP summer school, I can analyze using 2 continuous variables with this script. However, when I try using 3 variables (2 continuous 1 dummy coded), I get stuck while setting up the matrix. Before starting the analysis, I standardized my variables so that the SDs were 1 and their mean was 0.
Part of my code is as follows:
nv <- 3 # number of variables for a twin
ntv <- 2*nv # number of variables for a pair
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model

variable

NTFD without zygosity information
is it possible to estimate a NTFD without zygosity information? I know from other twin models that they can be adapted to this type of data. Is it also the case for the NTFD? If so, how would one adapt the script in OpenMx?
Best,
Mirko
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Multivariate binary-continuous twin model
Hi,
I am currently working on a multivariate correlated factors twin model with combined binary and continuous traits. I have six variables in total, the first two being binary data and the remaining four being continuous. I have been struggling for a while now in extracting meaningful output, specifically for the aetiological correlations. I receive genetic correlations with corresponding confidence interval lower bounds that are higher than the estimate itself (even though status is ok and model has converged).
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Twin Model Identification Matrix Algebra
I was reading the book by Neale and Maes (2004) and they have a nice part about how to check the identification of a univariate twin model using matrix algebra (p. 104).
It is possible to check the identification of the model by representing the expected (co-)variances as a system of equation in matrix algebra:
Ax=b
where x is the vector of parameters, b is the vector of observed statistics and A is the matrix containing the weights of elements in x.
In the univariate case (ACE model), x=(a^2,c^2,e^2).
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Causal Common Contingent Modeling Code Help
I'm working on a model of smoking quantity given initiation of regular smoking along the lines of Bares, Kendler, and Maes 2015 among others. I'm having a bit of trouble figuring out how to move from a more straightforward bivariate model to the CCC model by implementing the estimated path from initiation to quantity. For reference, this is designated b in Figure 1 at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4631696/
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Troubleshooting Error Message - MxTryHard()
##I'm running the univariate ADE model using Hermine's script.
##When it comes to testing the assumptions of equal means and variances, I keep getting the following error message:
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Re-Randomize Twin Order
Thanks!
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