OpenMx Help
PaulTwin
Joined: 01/29/2017
Error in svd(X) : infinite or missing values in 'x'
Dear OpenMx-ers,
For my research, I am running a latent variable model with an interaction effect between two latent variables on a latent outcome variable, all measured by ordinal and skewed manifest variables. I use WLS estimation and the matched pairs approach (Marsh et al., 2004) to model the latent interaction. I attached two simulated datasets:
* forumdata1: the true size of the latent interaction is 0
* forumdata2: the true size of the latent interaction effect is .04
PaulTwin
Joined: 01/29/2017
Error in t(jac0C) %*% W
Dear OpenMx-ers,
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lior abramson
Joined: 07/21/2017
Ordinal covariance is not positive definite in data
Hi,
I would like to ask for help with an error:
Details about my openMX run:
OpenMx version: 2.7.12 [GIT v2.7.12-dirty]
R version: R version 3.4.1 (2017-06-30)
Platform: x86_64-w64-mingw32
Default optimiser: CSOLNP
I am trying to run a univariate model with three covariates-one categorical and two continuous. Unfortunately, when I get to the phase of model running (mxRun), no matter what I do, I receive the following error:
lior abramson
Joined: 07/21/2017
error code 6 in Univariate ACE model- Could it be related to missing data?
Hello,
I would like to ask for help with an error code 6:
Required details about my openMX run:
OpenMx version: 2.7.12 [GIT v2.7.12-dirty]
R version: R version 3.4.1 (2017-06-30)
Platform: x86_64-w64-mingw32
Default optimiser: CSOLNP
cjcook
Joined: 05/22/2017
LISREL Simulation
Hello,
I am trying to simulate data using the endogenous variables only LISREL model as seen on page 133 of the OpenMx.pdf help documentation. I was able to simulate data from a state space model using the example in the help documentation on page 174. Now I am modifying that piece of code for a LISREL model. However I am running into an error. Below is my code.
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Soyoung
Joined: 05/08/2017
multilevel path/structural equation models in OpenMx
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.
Shesprich
Joined: 04/13/2017
OpenMx Installation on Redhat Cluster
Greeting all,
I am attempting to install OpenMx on a x86_64 Redhat Linux cluster running R 3.3.1. I am installing it using the command source('http://openmx.psyc.virginia.edu/getOpenMx.R').
Based on the errors I am getting it looks as if R is not invoking a compiler. Here is the full output of what I am getting:
> source('http://openmx.psyc.virginia.edu/getOpenMx.R')
You are now installing the latest version of OpenMx.--- Please select a CRAN mirror for use in this session ---
HTTPS CRAN mirror
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Anne H
Joined: 03/30/2017
Problems with requiring OpenMx on Mac OS Sierra 10.12.3
Hi!
I'm having problems with requiring OpenMx. The installation process itself seems to go smoothly. I am running Mac OS Sierra 10.12.3 (macbook pro 15, mid 2015), R 3.3.3 and OpenMx 2.7.9.
I have tried loading OpenMx from cran/ package installer, but then OpenMx doesn’t seem able to run my script, due to missing NPSOL optimizer, as far as I’m able to understand from the error code. Any help regarding what I'm missing here, would be much appreciated :)
rabil
Joined: 01/14/2010
Error: Unknown reference 'rho' detected
I am trying to allow for correlation between some residual errors in a single common factor model with 7 methods. I want them to all equal a common correlation rho. The attached file shows how I coded the mxPath and mxAlgebra statements to link the covariances so that the covariance equals the product of the two standard deviations and the common correlation rho. When I run this using mxRun or mxTryHard:
fit.all.cov.deep2 <- mxRun(model.all.cov.deep2)
Error: Unknown reference 'rho' detected in the entity 'cov23' in model 'model_all_cov_deep2'
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rabil
Joined: 01/14/2010
Single Common Factor Model with Some Residual Errors Correlated
I want to fit a single common factor model to seven different types of measurements of the same thing. However, 6 of the methods I expect to have residual errors that are positively correlated. I expect the intercorrelations to be the same among these 6 methods (fortunately) so I want to build in this assumption. There would be too many correlations to estimate separately. So I want to assume rho is the same and need to constrain, say, cov23 = sigma2*sigma3*rho, cov24=sigma2*sigma4*rho, etc. But I don't see how to do this using mxConstraints.