# Behavioral Genetics Models

## Latent Growth Curves and Definition Variables in a Twin Sample

## Longitudinal Question

I am considering using a bivariate model to investigate the relationship between variable 1 and variable 2. Data is available for both variables for the same population for 2010 and 2016.

If I want to investigate this relationship longitudinally (the effect of variable 1 on variable 2) could I use a bivariate script with variable 1 in 2010 and variable 2 in 2016? or should I use a different model/script?

Thank you so much.

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## Bivariate Cholesky model with paths specification

I wrote a syntax for bivariate cholesky model for two variables measuring two different traits at the same time-point. However, I think that I may have missed something. In the output I see the ACE coefficients for each observed variable, but I do not see the the ACE coefficients to the covariance between the two traits (i.e. the coefficients that explain what part of the variance is explained by shared genetic and environmental influences on the two traits).

Do you know what I should add to the syntax in order to receive this output?

## Bivariate twin model（ACEorADE）

Recently, I have done a bivariate models.BUT I am confused with how to choose ACE or ADE in the bivariate models? I have tried using ICC in each variable apartly, BUT the fitting model one is ACE when another is ADE. NOW the question is that which one bivariate model I should use ? ACE-ACE or ADE-ADE or ACE-ADE? If the the answer is ACE-ADE, how to write the script?

Thanks for some help!

Cheers,

Fengxia

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## Twins raised apart + together

I do not know if this is the most appropriate section for posting however I will give it my best shot. I am conducting a capstone project for my genetic epidemiology program but unfortunately my mentors are unaware of the methods used for the project I will describe here so they encouraged me to connect with individuals on this website. Some may argue I should do a project that I can receive some assistance with from my mentors but I am passionate about this project!

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## Multiple testing

First of all, is any such correction really needed for 9 outcomes?

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## doubt with binary variables

I am trying to do a joint analysis between 2 binary variables and 1 continuous variable I am having some problems to fix the variance for the 2 binary variables equal 1.

I think I should change something here

matUnv <- mxMatrix( type="Unit", nrow=nvo, ncol=1, name="Unv1" )

matOc <- mxMatrix( type="Full", nrow=1, ncol=nv, free=FALSE, values=oc, name="Oc" )

var1 <- mxConstraint( expression=diag2vec(Oc%&%V)==Unv1, name="Var1" )

NVO=2

NV=3

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## Rationale for Bootstrapping CIs

Is there a rationale for bootstrapping 95% CIs for univariate ACE estimates when relying on a relatively small convenience sample of MZ/DZ twins? Any source(s) that would support doing so?

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## Moderation Model

I am trying to fit a moderation model. I have modified one script but in this script the moderation variable is the same for twin1 and twin 2 (age). I want to fit a moderation model with 1 variable with different values for twin1 and twin2 (like IQ). I have done all the changes but I am not sure if it is correct. Specially this line:

meanG <- mxAlgebra( expression= cbind((int + DR1),(int + DR2)), name="expMeanG" )

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## Direction of causation model

I have a question regarding the Direction of Causation (DOC) model. I have found a very useful script at the following link and I'm trying to modify it according to my dataset: http://ibg.colorado.edu/cdrom2016/verhulst/Causation/DOC%20student.R.

I have 2 observed variables (x and y, both continuous) and I would like to verify if their association is causal (i.e. if x causes y. The inverse direction is not possible as x comes before y).

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