OpenSEM Forums
Fengxia
Joined: 11/02/2017
Bivariate twin model（ACEorADE）
Hello,
Recently, I have done a bivariate models.BUT I am confused with how to choose ACE or ADE in the bivariate models? I have tried using ICC in each variable apartly, BUT the fitting model one is ACE when another is ADE. NOW the question is that which one bivariate model I should use ? ACE-ACE or ADE-ADE or ACE-ADE? If the the answer is ACE-ADE, how to write the script?
Thanks for some help!
Cheers,
Fengxia
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esei
Joined: 08/05/2016
Multilevel model
Hi all!
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oscarrob
Joined: 03/10/2018
Twins raised apart + together
Ciao all,
I do not know if this is the most appropriate section for posting however I will give it my best shot. I am conducting a capstone project for my genetic epidemiology program but unfortunately my mentors are unaware of the methods used for the project I will describe here so they encouraged me to connect with individuals on this website. Some may argue I should do a project that I can receive some assistance with from my mentors but I am passionate about this project!
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Tom Rosenstrom
Joined: 03/01/2018
Pairwise maximum likelihood estimator available?
Hi.
This is probably a good place to ask if anyone has implemented the new pairwise maximum likelihood estimator for Open Mx? For example, this paper mentions that "PLM fit estimates can also be obtained with Open Mx":
https://doi.org/10.3389/fpsyg.2016.00528
Veronica_echo
Joined: 02/23/2018
Ch11_Kevin J. Grimm, Nilam Ram, Ryne Estabrook_Growth Modeling Structural Equation and Multilevel Modeling Approaches
Hi everyone,
I am trying to estimate the knot of piecewise latent growth model and using one piece of code from Grimm, Ram & Estabrook's book as my reference (P268-269). However, it reported an error "Error: Illegal label 'L10[1, 1]' detected in matrix 'A'. Square brackets must contain numeric literals when used inside of labels."
matthewcgraham
Joined: 02/20/2018
Bootstrap Likelihood Ratio Test
I'm interested in using the new bootstrap function in mxCompare to evaluate nested growth mixture models (GMM) using the Bootstrap Likelihood Ratio Test (BLRT), but am a uncertain how to do so. For example, in the attached code building on the GMM example provided in the OpenMx documentation, say I wanted to compare a three-class model to a two-class model. How would I conduct the BLRT?
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alha9497
Joined: 01/29/2018
Fitting SEMs from correlation matrices and standard errors
Hello,
I have two general questions and I am particularly interested in doing these models in OpenMx.
1. Is there a way to estimate SEMs with input only being pearson's correlations and the standard errors from the pearson correlations? I want to do this without back transforming to the sample size, so essentially the sample size is unknown.
JBosdriesz
Joined: 03/07/2017
Multiple testing
One of my Phd students recently received reviewer comments for a submitted paper in which she presented 9 univariate ACE models on separate outcome measures. One of the reviewers asked: “Please indicate how correction for multiple comparisons was handled for the genetic modeling. Given that several brain regions were being analyzed, what statistical threshold was used?”
First of all, is any such correction really needed for 9 outcomes?
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JuanJMV
Joined: 07/20/2016
doubt with binary variables
Hi everyone,
I am trying to do a joint analysis between 2 binary variables and 1 continuous variable I am having some problems to fix the variance for the 2 binary variables equal 1.
I think I should change something here
matUnv <- mxMatrix( type="Unit", nrow=nvo, ncol=1, name="Unv1" )
matOc <- mxMatrix( type="Full", nrow=1, ncol=nv, free=FALSE, values=oc, name="Oc" )
var1 <- mxConstraint( expression=diag2vec(Oc%&%V)==Unv1, name="Var1" )
NVO=2
NV=3
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chancey
Joined: 09/09/2017
Rationale for Bootstrapping CIs
Hi all,
Is there a rationale for bootstrapping 95% CIs for univariate ACE estimates when relying on a relatively small convenience sample of MZ/DZ twins? Any source(s) that would support doing so?
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