Categorical Outcomes

hello, Everyone!

I would like to seek for your help for the code. I would like to model a two-factor Cholesky decomposition using 1 continuous and 1 binary variable in the model. Your help is highly appreciated!

Hi,

I am currently working on a saturated model with 6 groups (mzm, dzm, mzf, dzf, dosfm, dosmf) and a dichotomous outcome variable (with one threshold). See part of the saturated model below.
I have fitted 1 dichotomous definition variable in this model. At the first try it didn't work and after reading one of the previous threads I figured out that this is because the definition variable cannot have missings in OpenMx.

Delete post.

Does the new OpenMX version allow me to model a Four-factor Cholesky Decomposition? I would like to use 2 continuous, 1 ordinal, and 1 dichotomous variable in the model? I was wondering if anyone might have code that is similar to post on the forum for 3 or 4 factor models? Below is my attempt but I get NaN for the standard error.

#vars v1 and v2 are continuous and v3 is ordinal (5 categories), but v4 is dichotomous
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nvar <- 4 # number of variables
tnvar <-8 # number of variables*max family size

Hello,
What are my options when doing twin modeling on a multinomial variable (e.g. what is your favorite wine?: 1) red; 2) white; 3) rosé; 4) sparkling), and there is no hierarchical structure between the categories? That is, how do I best use the cross-twin information that co-twins of sparkling wine drinkers prefer rosé over red wine?

If an ordinal variable has 20 categories, is it practical to try to handle this with thresholds? Or would it be better to treat as continuous?

I am fitting a model with one binary variable and one latent variable. The goal was to estimate the threshold (and then the proportion) of the binary variable. The following syntax worked in OpenMx 1.1.2 but failed in OpenMx 1.2 beta. Attached are the output.

Any suggestions? Thanks in advance.

Mike

######### Fitting a binary variable
library(OpenMx)
## Create n=100 binary data with p=.6
my.df <- data.frame(x=c(rep(0,each=40),rep(1,each=60)))
## Starting value for the threshold
st <- qnorm(colMeans(my.df))
my.df$x <- mxFactor(my.df$x, levels=c(0,1))

Hi,
I'm fairly new to OpenMx and twin modelling. I have completed the twin modelling summer school at the SGDP this year, where we have learnt how to run a univariate liability threshold model. We have now tried to expand this script to a bivariate model, however we have only been able to make it work until the saturated model. Would anyone be able to let us know how to further expand the script so that it also works for the remaining ACE, AE etc models and what else we need to adjust so that it work for a multivariate (common pathway) liability threshold model.

I am brand new to OpenMX. I have been using Mplus. Could anybody show me how to fit an exploratory factor analysis model using binary indicators? Thanks.