Behavioral Genetics Models

How does one make the variance estimates a function of the definition variable sex? I am working on a univariate script with two groups, MZ and DZ, with opposite sex twins included in the DZ group. I have tried to apply principles from the moderator script from Boulder, but I'm not sure if that is OK for the definition variable case. The script below fails due to inconformable arrays, and I am working on getting the matrices in the right format, but I need to know whether I am on the right track here. Very grateful for any help to get some steps further.

Hi,

This isn't concerning OpenMx per se, but rather a general twin analysis question.

My variables are PC scores from a decomposition of shape data. Normally for one variable, you'd calculate an ICC for MZ and DZ groups to show if there is greater similarity for MZ's, prior to more formal modelling. My data needs to be analysed together instead of testing each variable/PC separately. Is there a multivariate equivalent of the ICC - ie something like partial least squares or canonical correlations?

Thanks,

Paul

Hi,
I am testing submodels under a multivariate (3 variables) common pathways ADE model. I want to run a submodel where I drop the specific d for the first of the three variables, but I keep getting error messages. I hope someone could help me out with this.

I have tried various versions of the procedure below:

multiComPathAEad1eModel <- mxModel(ADE_Common_Fit, name="multiComPathAEad1e",
mxModel(ADE_Common_Fit$ADE,
mxMatrix( type="Diag", nrow=nvar, ncol=nvar, free[1,1]=FALSE, values[1,1]=0, name="ds" )
)
)

Hi,

I've tried setting up an ACDE model as I have siblings (up to 3) data for my twins.

Sorry, basic question but I've managed to confuse myself with how to interpret best fit. I've embedded all submodels within the ACDE model. As per below, the AE model has the lowest AIC, so that is the best fit right? So the p value is lower than the ACE model because of the extra df compared to the main model?

> # Compare all models
> ACDENested <- list(multiCholACEFit,multiCholADEFit, multiCholAEFit, multiCholCEFit, multiCholEFit)
> tableFitStatistics(multiCholACDEFit,ACDENested)

I am a new user of OpenMx , this is my first post.

I am trying to calculate Confidence Intervals on standardized estimates (univariate model). To use the function: mxCI() the standardized estimates have to be defined inside the model.

Does anyone know how to define the standardized estimates within the model so that I can request them in the CI function?

Thanks in advance for your help.

Maria

Hi
In old Mx I used the following command to make a correction in degrees of freedom for equality constraint groups:
opt df=-18 ! df correction for each constrained group: (nvar*nvar+1)/2

How would this be performed in OpenMx?

I have a set of continuous measurements from MZ/DZ pairs, and data acquisition was done in two successive sessions. I am interested in estimating genetic, shared and unique environmental components. It seems an ACE model with repeated measurements would be appropriate here.

Is there any available example script for carrying out this kind of analysis with openMx?

Anyone who has a well-functioning OpenMx script for running multivariate ACE/ADE with sex as a moderator (general heterogeneity) (including constrained Cholesky, independent pathways and common pathways models) that they would be willing to share as an example script?

I find it hard to adapt existing univariate scripts and be sure I do everything right. It would be very reassuring to have a mulitvariate script to validate one's own against.

Hi,

I'm stuck with how one sets up their data frame to take into account relationships beyond that of twins (in my case - sibs and triplets).

For a standard twin model - your data is 'wide' formatted:

ie Var_t1 Var_t2
... ...
... ...

How do you do this for sibs - the closest I can think is to model a sib against each of their twin siblings, something like:

Var_t1 Var_Sib
Var_t2 Var_Sib for one family, then

Var_t1 Var_Sib
Var_t2 Var_Sib for another family, etc

and treat the relationship as you do for a DZ pair.