OpenMx Help
rabil
Joined: 01/14/2010
Residual Variance as a Function of a Latent Variable
Imagine you have a simple one-factor measurement error model - just one latent variable u with say 5 indicators. How would you make the residual variance of the indicators a function of u? For example, a linear function of u. Is this possible using OpenMx?
rabil
Joined: 01/14/2010
Constraint Not Honored
I have a simple two-factor measurement error model. There is a constraint on the variance of one of the latent factors that it be positive. It easily finds a solution using mxTryHard but the variance estimate is always negative. What is the point of using a constraint if it is not honored? The negative estimate then causes problems when I try to bootstrap confidence intervals. It complains about quantile missing values and NaNs and won't produce a result unless I remove the variance from the confidence interval list.
- Read more about Constraint Not Honored
- 10 comments
- Log in or register to post comments
cjvanlissa
Joined: 04/10/2019
MxModel returns class MxRAMModel instead of MxModel?
I'm calling MxModel via do.call, with a list of arguments. Previously, this consistently returned objects of class MxModel. Now (probably after the latest OpenMx update), it returns MxRAMModel, which is inconvenient because not all exported methods work with MxRAMModel.
I'm rolling back my installation of OpenMx now to check if it's due to the latest update, but that takes a while.. in the meantime - does anyone know why I'm getting MxRAMModels and how to prevent that?
jmatosv
Joined: 04/25/2015
Model identified at solution but not identified at start values
Openmx follows an iterative method when executing mxCheckIdentification function. Therefore, on first iteration start values are used to solve model equation; then, the iterative process continues until the best (optimal) solution is obtained.
If we run mxCheckIdentification(pathrun) and the model is locally identified at solution, but we run mxCheckIdentification(pathmod) and the model is not locally identified at start values, would that be a reason of concern when evaluating the model?
Sedat KANADLI
Joined: 08/15/2022
Residual Covariance Matrix
Dear Mike,
A colleague and I studied the factor structure of a scale using the metaSEM package. The reviewers asked us for residual covariance matrice of structural model we construct. I couldn't see a command for this in the metaSEM package. There is vcov but this command gives sampling covariance matrices. Is there a way to see residual covariance matrices?
Sincerely
- Read more about Residual Covariance Matrix
- 7 comments
- Log in or register to post comments
hansfredriksunde
Joined: 12/10/2021
Weird model comparison results when using WLS
UPDATE!
Roya
Joined: 10/25/2021
Non-positive definit matrices
Hello Mike,
I am applying the MASEM method to 70 articles to find the direct and indirect effects of a variable (I have only three variables, one outcome, one exposure, and one mediator). I have 67 non-positive definite matrices. I understand that excluding all those matrices is missing lots of data. What should I do in this case? I did the analysis, ignoring the positive definite assumption, and I got the results but I don´t know how reliable are the results.
I´d be grateful if you please help me to find a solution for that.
- Read more about Non-positive definit matrices
- 5 comments
- Log in or register to post comments
pehkawn
Joined: 05/24/2020
Dealing with duplicated data in a multilevel model
I have two datasets of teacher and student data, each representing a level in a multilevel model. The teachers have a unique link to a student taught in one specific class, and teachers have unique response items for each class. On the other hand, each student have only a single entry and do not have unique data for each class. This leads to the issue that teachers may teach the same student in more than one class, which creates a duplicated entry of the student if the datasets are merged.
- Read more about Dealing with duplicated data in a multilevel model
- Log in or register to post comments
suzannejak
Joined: 01/06/2010
Equivalent of qnorm() and pnorm() in mxAlgebra?
Dear OpenMx team,
I would like to use the quantile and distribution function for a (not standard) normal distribution in an mxAlgebra, equivalent to using qnorm() and pnorm() in R. Does this exist?
Thanks in advance!
arinbasu
Joined: 06/09/2011
OpenMx fails to install under R-4.1.3 Linux, omp.h file not found error
I tried to install OpenMx in Void linux.
The R version is 4.1.3
(I have not installed 4.2.0 as it is not yet available on their servers and I did not want to install myself)
On install.packages("OpenMx"), it halts as it cannot find `omp.h` file.
However, `omp.h` file is present in the following location:
/usr/lib/clang/12.0.1/include/omp.h
How can I make sure that OpenMx installation can "see" this file?
Would greatly appreciate your guidance.
Best,
Arin