OpenMx Structural Equation Modeling
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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lf-araujo
Joined: 11/25/2020
How to go past a model implied cov not positive definite error?
Hi all,
I am trying to specify the CLPM in the attached figure (It's an extension of Zyphur's 2020 general CLPM, but with PGSs). I specified both using lavaan syntax in umx and matrix algebra (first time, hope it is correct, but looks like so). It is identified, the model runs ok. But when I try to get power or the ncp statistic it fails, as the model's implied cov is not positive definite.
- What can I do to avoid this? lbounds and ubounds will help me there?
Lavaan code:
pehkawn
Joined: 05/24/2020
Interactions in latent variable models
I am fairly new to SEM in general, and I've been trying to figure out the best approach to modeling interaction effects between latent variables in OpenMx.
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Mike Cheung
Joined: 10/08/2009
Comparing raw data and covariance matrix as inputs
Hi,
I am comparing the models using raw data versus summary statistics as inputs. First, let us consider a simple regression model (see the attached example). The model fit should be perfect with df=0. With the raw data as inputs, the chi-square statistic is 2.103206e-11, which is quite reasonable.
When the summary statistics (covariance matrix and means) are used as the inputs, the chi-square statistic is -0.01006717, which is relatively big.
Mike Cheung
Joined: 10/08/2009
Fixing the parameter estimates at the starting values
Hi,
I want to fit a model by using the starting values as the parameter estimates. This can quickly be done by treating them as fixed parameters. However, I also want to get some standard errors on these estimates though the starting values may not be the optimal solution.
I can fix the starting values as the estimates with `mxRun(my.model, useOptimizer = FALSE)`. But it does not provide any standard errors. Attached is an example. Any suggestions? Thanks in advance.
Mike
Andre Achim
Joined: 02/10/2021
mxCI() not providing the confidence intervals. Why?
mxCI() not providing the confidence intervals
jpritsker
Joined: 09/27/2020
How does OpenMx handle missing data with WLS?
I might be missing something obvious, but as far as I can tell, this isn't explicated anywhere. How does OpenMx deal with missing data for WLS? Is it listwise/pairwise or is the polychoric covariance matrix computed using FIML?
ywsky01
Joined: 08/06/2020
Confidence intervals of ACE model fit
Hi all,
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Jannik
Joined: 10/01/2018
Custom Optimizer in OpenMx
Hello,
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Mike Cheung
Joined: 10/08/2009
CIs on mxAlgebra
Hi, all.
I have a mxAlgebra of a parameter multiplied by a constant, say new_x = 2*x. When I construct an LBCI on both x and new_x, I expect that the CIs on new_x are the same as the CIs on x multiplied by 2. It turns out that they are not exactly the same (see the "diff" in the following output). When the constants are larger, say 5 or 10, the CIs on the new_x even become NA.
Any ideas why this happens? Thanks.
## Multiplied by 2
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