OpenSEM Forums
janajarecki
Joined: 06/26/2019
Mixed-effects mediation example in openmx?
Hi there,
thank you so much for developing openmx, it's fantastic and flexible.
Do you probably have an example for openmx for a
(i) mediation model in openmx, or
(ii) mediation in a mixed-effects model [at the cluster-level or the within-cluster-level]
(Couldn't find any on the page here nor google).
Cheers, and thank you!
Jana
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rranne2@uic.edu
Joined: 12/10/2018
Finding R-squared for two different models
Hello!
I have a question about how to calculate r-squared for two different kinds of models. One is correlational and the other models change over time, with just two time points. They both include latent constructs, with anxiety and depression in both models as latent variables derived from four items each. The models are identified and have a relatively good fit CFI of .944 and .954, respectively.
1) "Plan E" Correlational Model (attached visual)
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chancey
Joined: 09/09/2017
Modeling Suggestions for Experimental Data
Question for the group: How might one go about modeling experimental data with twin respondents?
I ran a single-factor survey experiment with a small group of twin respondents (MZs and DZs, mainly same sex). There were two conditions. I randomly assigned twins to receive either:
Conditions A A
Conditions B B
Or
Conditions A B (or B A)
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JBosdriesz
Joined: 03/07/2017
Age as covariate or moderator
I looked around the forum, and found referrals to a post that might address this issue, but that page wouldn't load anymore, so I thought I'll post my question here.
I'm running a set of univariate ACE models, on a range of outcomes. I have two age groups (3-4 and 7-8), that I would like to analyse separately, by also combined.
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camus
Joined: 03/21/2019
Obtain 95%CI for ACE model- script revised from Dorothy Bishop
Hi, I am new with R and OpenMx. Recently I revised Dorothy Bishop's script to run ACE models. However, her original code could not get the 95%CI for of A,C,E estimates, but only 95%CI for Unsquared path estimates. I know mxCI() can obtain 95%CI, but after various attempts, it never works for me. Could any expert have a look of the code and let me know how should I add it?
Thanks!
diana
Joined: 04/17/2019
I am wondering if define variables will decrease E and increase A?
I am wondering if too many define variables will decrease E and increase A?
For instance, I want to estimate the heritability of coronary heart disease (CHD), should I adjust all the risk factors of CHD as much as possible, such as smoking, drinking and BMI? I'm afraid that it will overestimate A and underestimate E since I saw a revelent [paper](https://www.ncbi.nlm.nih.gov/pubmed/15520515/).
Many thanks!
rranne2@uic.edu
Joined: 12/10/2018
negative variance in factor representing change in anxiety (latent factor)
Hello there!
I'm having trouble with a model investigating change in anxiety over time. In the future, I will be building out a more complex model with other factors predicting change in anxiety over time, but I'm now just at a step before that looking into a model with only change in anxiety over time--only for two time points.
Qiuzhi Xie
Joined: 12/27/2018
About the overlap on the genetic and shared environmental factors
I am conducting the Cholesky model and wondering how to judge if two phenotypes significantly overlap on a genetic or environmental factor. It should be judged by the loading factor and the 95% CI, right? In the following example, only the third phenotype (P3) does not significantly overlap with the others on the A1 (genetic) factor, as the lower boundary of the 95% CI is smaller than .00. Am I right?
diana
Joined: 04/17/2019
GxE model for binary variable
Hello! I am trying to fit a GxE model. The phenotype is a binary variable, and the moderator is measured on a 6-point scale .
I want to use the code posted in [there](http://ibg.colorado.edu/cdrom2016/franic/Moderation/Practical/DO_NOT_OPEN_Moderating_covariances_practical_solved.R), but this code is suit for continuous variable and I don't know how to change it to be suit for binary variable. Could you tell me what lines I should change or add?
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Vivifj03
Joined: 04/25/2019
Two-parts mixed effects model for longitudinal data with mixture distribution for random effects
Hi you all,
My outcome variable is a semicontinuous variable measured over time with a bunch of zero values. Since it is continuous data I cannot use poison or other zero-inflated models. However, I am implementing a two-parts model. The first part is a logistic mixed effects model for modeling the zero currency. Then, the second part is a linear mixed effects model. Now, there are two main issues. First, the random effects of both models are correlated. Second, the distribution of the random effects is a mixture of normal distributions.