OpenSEM Forums

Hello

Does anyone have an ACE script for enabling the variance for twins 1 and 2 to be estimated separately (and separately for MZ and DZ twins) to deal with heterogeneity in their variance?

(or even just the adjustments that need to be made to the standard script?)

Thanks so very much

Karen

Hi,
Are there any example scripts for how to add a definition variable to a RAM model, and how to then use that in an algebra on a path?

Here's one adding a definition variable for means, but not including its value in an algebra, and then using that algebra to se the value for another path.

[https://openmx.ssri.psu.edu/docs/OpenMx/2.5.1/DefinitionMeans_Path.html](https://openmx.ssri.psu.edu/docs/OpenMx/2.5.1/DefinitionMeans_Path.html)

Hi,

Could we run a bivariate heritability analysis using twin data when one of two traits has a best model ADE or DCE and the other ACE?
Two main phenotype seems to be more ADE for one and DCE model for the other and I compare them with other phenotypes with different best model.
One of my colleague has kindly provided to me her script but it runs only when the two traits have a best model type ACE.

I know that Ra, Rd could be null as one of my phenotype didn't have it in its best model. It is fine, but at least the model for each trait is the best.

Hi,

It seems that OpenMx uses the same formula of RMSEA for both single- and multiple-group analyses. According to Steiger (1998), the RMSEA should be adjusted by a factor of sqrt(K) where K is the no. of groups.

The attached PDF includes the test suggested by Steiger (1998, p. 417):
1. Construct two identical arbitrary data sets (random numbers will suffice).
2. Test one sample with a simple model, for example, a single factor model, and record the RMSEA value.

Hi there,

I am working with twin data. My current analysis involves data that has a lot of variation, and I am using small numbers n=90 MZ twins and n=48 DZ twins. I am working off a univariate ACE script and I am getting the CE model as the best fit for variables where the MZ correlation is significantly higher than the DZ, I would expect some heritable component.

Hi,

I would appreciate some advice on what model I need to use in order to test some specific hypotheses. I have suggested some ways to do this, but not sure if it is doable or correct

I have three traits, with phenotypic correlations of around .40.

Hypotheses:
1- large genetic correlation between trait 1 and trait 2 and 3
2- Much of the genetic variance component of trait 2 and trait 3 can be explained by the interaction between environmental variable B and common genetic factors of trait 1&2&3.

I thought I could maybe try the following analyses:

Hello! This is a follow-up post to some guidance I got on this board awhile ago that was incredibly helpful. I am trying to run a bivariate saturated model that controls for age and sex. The two variables were assessed at different time points, so one variable needs to be adjusted for age1 and sex, the other variable for age2 and sex.

Hi, I'm very new to openMX and I'm trying to analyse a bivariate analysis (one variable quantitative and one categorical).
But In the saturated model, there are significant differences in "Constrain expected Thresholds to be equal across twin order and zygosity" . When I remove oposite sex twins the differences between models there aren't significant.
I would like to know what model should I use.
*there are differences between men and women in the categorial variable.
A sex limitation model? or remove Oposite sex twins?
Any example or guiding light will be very appreciated.

Hello,

I'm trying to understand the support OpenMx has for nested models and especially cross-classified models. I've found some great examples (http://psychological-research.org/R/) for doing these models in a wide data format. This approach though is a bit cumbersome for larger and more complex models, especially cross-classified models.

I can't find any examples using a multiple group approach (e.g. Muthen, 1994). Can OpenMx use this approach? Are there examples?

Hi there,

I'm very new to OpenMx and working with twin data (OpenMx version: 2.5.2 [GIT v2.5.2] R version: R version 3.2.4 Revised (2016-03-16 r70336) Platform: x86_64-w64-mingw32 Default optimiser: SLSQP).

I created a script based on online resources from this site, where I want to run saturated, ACE and submodels, controlling for age and gender.

As far as I can tell, the script is running, with no warnings/ errors. However, I am getting p values of 0 for the Chi square difference test for the ACE model compared to saturated. I am wondering if this is alright/ presentable?