OpenSEM Forums

Multivariate moderation
I'm an undergrad working on my dissertation, and I've managed to build my first models thanks to these forums, the Boulder Workshops, as well as [Hermine's wonderful stash of scripts](https://hermine-maes.squarespace.com/). I have several questions, however, just to make sure I'm doing things the right way, and if what I want to do is possible.
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when to standardize?
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impact of ignoring higher level clustering
I've read before that when cases are nested, ignoring the clustering generally affects standard errors but not the regression coefficients. Is this the case for ACE model parameters as well, e.g., when twin pairs are nested in schools or geographic regions?
Thanks!
George
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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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Individual slope and intercept estimates?
My inclination is to get factor score estimates for the intercept and slope factors, but when I do this using mxFactorScores(), I get an error message:
"Error: In model 'FactorScoresLGCM_N' the name 'fscore' is used as a free parameter in 'FactorScoresLGCM_N.Score' but as a fixed parameter in 'FactorScoresLGCM_N.Score'.
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Row wise log-likelihood contributions from classes
We are working on calculating Vuong LRT between mixture models from OpenMx. Specifically, we are adjusting the function vuongtest() from the package nonnest2.
But we are stuck in one step so far, getting the row-wise log-likelihood contributions to the overall model LL. Because of the structure on OpenMx we are able to get the row-wise contributions for each class, but we havent been able to see how these are combined into the overall model fit

family link functions v. threshold model on polychoric
I found one years old [Q&A](https://openmx.ssri.psu.edu/node/4678) in this forum here stating the the threshold model was akin to the probit. And this other [Q&A](https://openmx.ssri.psu.edu/thread/4074) mentions how to specify a probit model. So I am asking this question for a clearer answer.
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