OpenMx Structural Equation Modeling
pehkawn
Joined: 05/24/2020
Interactions in latent variable models
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Mike Cheung
Joined: 10/08/2009
Comparing raw data and covariance matrix as inputs
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.
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Mike Cheung
Joined: 10/08/2009
Fixing the parameter estimates at the starting values
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?
jpritsker
Joined: 09/27/2020
How does OpenMx handle missing data with WLS?
ywsky01
Joined: 08/06/2020
Confidence intervals of ACE model fit
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Jannik
Joined: 10/01/2018
Custom Optimizer in OpenMx
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Mike Cheung
Joined: 10/08/2009
CIs on mxAlgebra
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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Mike Cheung
Joined: 10/08/2009
CFA with categorical variables
I am fitting some CFA models with all categorical variables with FIML. The information matrix is often not positive definite when the number of variables is larger than 4 or above. Attached are some examples.
Any suggestions to improve its stability? Thanks in advance.
Best,
Mike
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blazej
Joined: 11/20/2018
Help in translating a longitudinal path model to OpenMx SEM syntax
As I'm new to SEM (in general) and OpenMx I would like to ask you for some help in specifying the model in question properly.
I'm trying to reproduce results for a 3 time points path model where specific indirect effects where of interest. The original model was depicted as in attached image.