OpenMx Structural Equation Modeling
Ben
Joined: 06/20/2023
Problems with non-convex Hessian with multilevel SEM
As written in this thread, I have repeated problems with a non-convex Hessian while working my way step-wise towards a 3-level SEM with latent variables and their respective measurement items in a paper in organizational psychology.
While I'm looking for general guidelines to deal with non-cenvex Hessians and status code 5-issues in that thread, it's probably good to look at my models to find issues here.
Ben
Joined: 06/20/2023
General strategies to deal with non-convex Hessian matrix
Hello everyone!
I am working on a org psych paper that is currently under review. **The model** is a quite complex *multilevel mediation SEM*, featuring *four latent variables* (only one is exogenous/independent, the others are endogeneous mediators/outcomes). I also include the *measurement models* for each variable (i.e., the respective items as manifest variables). Until now I have done the estimations in a 2-level model using lavaan. For the review I am trying to add a third level to control for further nestedness.
pehkawn
Joined: 05/24/2020
Understanding runHelper() error: MxExpectationRAM: latent exogenous variables are not supported
I've been trying to modify [this example](https://github.com/OpenMx/OpenMx/blob/master/inst/models/nightly/mplus-…) from OpenMx' repos for testing. For this purpose, I am trying to fit the model using WLS. However, this returns the following error message:
Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, :
MxExpectationRAM: latent exogenous variables are not supported (x -> sw)
Hasan
Joined: 03/07/2023
Moderated bivariate ACE
Hello,
I'm trying to fit a moderated bivariate ACE model such as the one seen in the attached picture.
Is there a way to do this in umx? As far as I can tell, neither umxGxE nor umxGxEbiv do exactly this. Can they be expanded to fit this particular model?
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cjvanlissa
Joined: 04/10/2019
How to specify a random intercept cross-lagged panel model in OpenMx?
Dear readers,
I am trying to specify an RI-CLPM in OpenMx. However, if I constrain the variance of the observed indicators to zero, the model implied covariance matrix is not positive definite - but these variances are supposed to be zero, as they are partialized into a time-invariant component and a time-variant component. E.g., the variance x1 <-> x1 should be split up into RIx <-> RIx and cx1 <-> cx1.
Can anyone help me correctly specify this model in OpenMx?
ppl
Joined: 01/12/2023
Maximum Likelihood for Cross-Lagged Panel Models with Fixed Effects - Allison et al. 2017
Hey all,
I just started recently to use OpenMx for academic reasons. I'm currently trying to reproduce the empirical example of the paper of Allison et al. 2017 in which they use a Maximum Likelihood Structural Equation Model (ML-SEM) for dynamic panel models.
The authors provide the code of the following software packages: R-lavaan, Stata, Mplus, SAS-Proc Calis. However, I'm using OpenMx in R since it seems to be more flexible for changes and adjustments than lavaan.
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
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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.
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iana
Joined: 10/16/2021
How to handle missing data in multilevel meta analysis & mutilevel TSSEM?
Hi Mike and all,
I'm working on a meta-analysis examining the mediators between attachment and intimate partner aggression. I would like to use two methods to meta-analyze the data. The methods include 1) three-level meta-analytic models (Assink & Wibbelink, 2016) and 2) three-level TSSEM (Wilson et al., 2016). Both are random-effects models.
cllstrauss
Joined: 04/07/2022
Random factor loadings in MCFA
Apologies if this is answered elsewhere, but I was wondering if OpenMx allows estimation of random factor loadings at the within-level in a multilevel confirmatory factor analysis.
A less important aside: has anyone been able to successfully include a nonlinear constraint in a two level CFA or SEM with latent variables?
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