OpenMx Help

Hello,

I'm developing a model, but I run into a couple of problems. Since the OpenMx documentation did not give the answer I was looking for, I want to try it here. I'm having a hard time getting started with SEM and with OpenMx because there is no real good overview of SEM methodology in my opinion.

I'm trying to run the following code:

library(OpenMx)

model <- mxModel(
name="Model",
type="RAM",
manifestVars = c("A", "B", "C", "D", "E","F"),
latentVars = c("var1", "var2", "var3", "var4"),
mxPath(from="var1",to=c("A", "B", "C")),

Hi,

Just tried to install OpenMx and encountered the following error:

> source('http://openmx.psyc.virginia.edu/getOpenMx.R')
Installing package(s) into ‘/usr/local/lib/R/site-library’
(as ‘lib’ is unspecified)
Error in ret[i, ] <- c(pkgs[i], lib, desc) :
number of items to replace is not a multiple of replacement length

I have R version 2.13.0 on Ubuntu 10.10 (32 bits)

Thanks for any help in advance.

Hello!,
I have prepared a script to compute a factor model (path diagram for Phillips and Fulker model ) of phenotypes of parents and twin children given by Neale.

I get an error message indicating the following sentence:
+ mxAlgebra( expression= (A%*%(S%*%t(C)))+(C%*%(t(S)%*%t(A))), name="J" ),

# MZ Twin
+ mxAlgebra( expression= (A%&%G%)+(C%&%R%)+J+(N%*%t(N)), name="U1" ),

Error: unexpected '&' in:
"mxAlgebra( expression= (A%*%(S%*%t(C)))+(C%*%(t(S)%*%t(A))), name="J" ),
mxAlgebra( expression= (A%&%G%)+(C%&"

Hello,

I was wondering if there is an easy way to tell OpenMx to estimate all of the correlations among a set of exogenous variables, rather than specifying each of the correlations line-by-line in mxPath statements.

For example, suppose exogenous variables are:
IVs <- c("COREREL", "JOBPAY", "SEX_2")

I tried to automate a way to include the exogenous correlations for an arbitrary number of variables as:

These.Pairs <- combn(IVs, 2)
Here <- NA
for(i in 1:dim(These.Pairs)[2])
{

Summer School at King's College will teach SEM for genetically informative datasets June 20-24 2011

http://www.kcl.ac.uk/schools/summerschool/si/sgdp/course1/

Hi!
I have a script for ordinal twin data that takes about 5-6 hours to compute in my laptop. I was wondering whether it would be beneficial in this particular case to parallelize the work in order to reduce the computational time. Would it be possible to adapt this script to do the job?

I have been reading the OpenMx notes in the manual to implement the parallelization with the "Snowfall" package, but they seemed a bit odd to me (I have not too much experience in parallelizing with R). Any indication would be very appreciated. I attach here the script if somebody wish to have a look.

Hi all,

Hi!

I have prepared a script to compute a linear growth model to estimate genetic and environmental influences (ACE) in an intake and a slope with ordinal twin data: 4 variables, 3 categories (2 thresholds) in each of them. The sample is is divided in 6 groups (and so is the script), according to zygosity and sex: MZ men, DZ men, MZ women, DZ women, DZ man-woman and DZ woman-man.

I get an error message indicating the following sentence:
> Error: The algebra 'ACE.expThre' in model 'lgcOrdACE' generated the error message: length of 'dimnames' [1] not equal to array extent