OpenMx Structural Equation Modeling

Hi,

Is it possible to estimate multilevel path/structural equation models with OpenMx?
If it is possible, is there an example code for multilevel mediation (path) model?

Attached files are the example of multilevel path model using Mplus.
Source: Heck, R. H., & Thomas, S. L. (2015). An introduction to multilevel modeling techniques: MLM and SEM approaches using Mplus. Routledge.

Hope I can do the same analysis using OpenMx.

Thank you in advance.
Soyoung.

Hey,
I work with OpenMx using a bit different data than most others; often data comes from a full population and has quite many rows (up to 3 million). A common type of analysis is for relatives with one or more binary variables, e.g. observed disease diagnosis, where the prevalence is low, e.g. 1% to 0.05%. The complexity of the models vary from simple 2x2 covariance matrices without any definition variables to 8x8 covariance matrices with several definition variables adjusting the means/thresholds.

Dear all,

I've met a weird issue with means running a simple model.

The data:
Cov<-matrix(
c(10,3.0,6.5,
3.0,10,6.5,
6.5,6.5,10),ncol=3,nrow=3)
library('mvtnorm')
data<-as.data.frame(rmvnorm(1000,mean=rep(100,3),sigma=Cov))
names(data)<-c('X','Y','Z')

The covariance matrix corresponds the model:
X -> Z = 0.5
Y -> Z = 0.5
X <-> Y = 3
X <-> X = 10
Y <-> Y = 10
Z <-> Z = 3.5
All means are 100

The model:
aModel<-mxModel(type='RAM',name='Phenotypic model',
manifestVars=c('X','Y','Z'),
mxPath(from=c('X','Y'),to='Z',connect='single',

The output below says a solution was found, but was it?

Begin fit attempt 21 of at maximum 21 tries

The path specification for an ordinal model in the documentation constrains the residual variances for the ordinal variables to 1. I would like to instead constrain the total variance for the ordinal variables to 1. But I'm not sure how to accomplish this. When the total variance is constrained to 1, there residual variance is constrained to 1 minus the factor loading squared (the factor loadings are constrained to be between -1 and 1) as I understand it.