OpenSEM Forums
valentinav
Joined: 06/15/2020
really similar AIC
Hi All,
I run the ACE model and submodels, and the AIC are really similar.
ACE 2579
AE 2577.5
CE 2577.3
E 2584
Overall, I always get a difference of 1 between the AIC.
The best winning model is always coherent with the results of the correlation analysis, so I tend to trust it, however, the difference is really little.
Is there a way to establish what is a significant difference between AIC?
Thank you all!
Valentina
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lemire
Joined: 12/13/2019
ACE: negative variance component from H.Maes’ published script and slides
Hi,
could you help provide some insights as to why running the following script, which uses data(twinData), gives negative estimates for Vc in an ACE model?
https://ibg.colorado.edu/cdrom2020/maes/twinModeling/oneACEvc.R
These are the most relevant lines related to the model:
inooradd
Joined: 03/11/2020
Step 1: Testing basic assumptions (equal means & variances for twin 1/twin 2 and MZ/DZ pairs)
Hello!
I am following the steps laid out in [this](https://vipbg.vcu.edu/media/course/HGEN619_2015/TwinModels.pdf ) openmx presentation and could use help with step 1.
1. Use data to test basic assumptions (equal means & variances for twin 1/twin 2 and MZ/DZ pairs)
valentinav
Joined: 06/15/2020
ACE model lower CI negative number
Hi All,
I am new to ACE model estimation so I am trying to follow some tutorials I found online (script attached).
The results seems fine, and are also coherent with another script I used. However, I got negative lower CI: ACEvc.VarC[1,4] -0.2443061 0.23255753 0.7557620.
Does this make sense to you? As far as I know when CI include 0 we cannot conclude that the value is different from 0...
I would really appreciate whether someone could help me with this.
Thank you in advance!
Best,
Valentina
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inooradd
Joined: 03/11/2020
Comparing ACE and ADE models
Hello,
I have a couple of questions regarding comparing ACE and ADE models.
1. Is there a quick method of comparing the fit of both of these models? As of right now I am running the scripts for each model, then comparing the two models using mxcompare:
<%
mxCompare( fitADENOTW , fitACENOTW ) %>
I know typically when we compare nested, we run something to the effect of...
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Benny
Joined: 05/15/2020
GxE with latent moderator
Hello,
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Leo
Joined: 01/09/2020
Bivariate Cholesky model with one continuous and ordinal variable
I'm new to OpenMx and I'm trying to understand the Boulder workshop scripts.
Particularly, I am trying to fit a model with one continuous and one ordinal variable. I have found this script but it is modeling only two ordinal variables:
http://ibg.colorado.edu/cdrom2016/maes/UnivariateAnalysis/twoa/twoACEoa.R
Is there a shortcut to only apply the threshold to one variable?
Thanks in advance.
JuanJMV
Joined: 07/20/2016
Interpret >1 and negative results from variance parametrisation of twin model
Hi All,
I am using the new parametrization for a bivariate model, as suggested in "Type I Error Rates and Parameter Bias in Multivariate Behavioral Genetic Models".
The results (see below) include an rA correlation that is higher than one.
Am I doing something wrong or I have to interpret the rA correlation as 1?
The phenotypic correlation is .2. Is it be correct to say that is due to 1, -.96 and .2 for A, D and E respectively?
There are also negative values: there is no way to interpret these results, right?
twolf
Joined: 04/24/2020
Should I ever need lower bounds in a twin model?
Hello,
I am currently starting to familiarize myself with different variations of the ACE-model as well as nuclear twin family designs in OpenMx and although coming from econometrics I dreaded working with SEMs so far I find the ride quite exhilarating.
While trying to reproduce certain results from the literature to broaden my understanding I sometimes encounter a strange behavior where I obtain a parameter estimate which is quite close to what I would expect with the only issue being that it is actually negative.
lior abramson
Joined: 07/21/2017
negative path estimate in UMX cholesky
Dear forum,
I conducted a Cholesky model with two variables in two time-points, using the uxACE command, and then conducted a model fitting procedure with the umxModify command. The model was an ADE model.
The results I got (a screenshot is attached) make perfect sense in terms of the overall explained variance by genetics. Meaning, if I compute the variance explained by both A and D for each variable (after squaring each path), I get the same amount of explained genetic variance as in the univariate models for each variable.
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