Behavioral Genetics Models
JuanJMV
Joined: 07/20/2016
bivariate model (problem in saturated model)
Hi, I'm very new to openMX and I'm trying to analyse a bivariate analysis (one variable quantitative and one categorical).
But In the saturated model, there are significant differences in "Constrain expected Thresholds to be equal across twin order and zygosity" . When I remove oposite sex twins the differences between models there aren't significant.
I would like to know what model should I use.
*there are differences between men and women in the categorial variable.
A sex limitation model? or remove Oposite sex twins?
Any example or guiding light will be very appreciated.
- Read more about bivariate model (problem in saturated model)
- 3 comments
- Log in or register to post comments
rebecca.barron
Joined: 07/01/2016
Viable chi square p values for ACE model comparison
Hi there,
I'm very new to OpenMx and working with twin data (OpenMx version: 2.5.2 [GIT v2.5.2] R version: R version 3.2.4 Revised (2016-03-16 r70336) Platform: x86_64-w64-mingw32 Default optimiser: SLSQP).
I created a script based on online resources from this site, where I want to run saturated, ACE and submodels, controlling for age and gender.
As far as I can tell, the script is running, with no warnings/ errors. However, I am getting p values of 0 for the Chi square difference test for the ACE model compared to saturated. I am wondering if this is alright/ presentable?
Jeremy
Joined: 03/25/2016
A Simple ACE Model that Seems to Be Failing...?
Hi, I'm trying to run a simple ACE Model that controls for age and sex. Searched the boards and found some recent posts that seem similar to what I want to do: http://openmx.psyc.virginia.edu/thread/4102
I tried to adapt it and this is what I've come up with:
# Select Variables for Analysis
Vars <- c('caster')
nv <- 1 # number of variables
ntv <- nv*2 # number of total variables
selVars <- c("caster1", "caster2")
mydata$ageT1[ is.na(mydata$ageT1) ] <- -999
mydata$ageT2[ is.na(mydata$ageT2) ] <- -999
Ell
Joined: 11/26/2015
Multivariate model with positive and negative correlations
Hi,
I am running a trivariate ACE Cholesky model where trait 1 and 2 are positively correlated, but trait 3 is negatively correlated with 1 and 2. The problem is that when I run the model, the upperbound CI's for the phenotypic correlation due to a, c and e is over 1 for some estimates (e.g. MZM.h2[1,3] ubound= 1.14034072)
I have 3 other similar analyses with different traits, with similar correlations and the same problem.
Any ideas how to fix this?
Thank you very much!
# -------------------------------------------------------------------------------------------------
svrieze
Joined: 01/03/2010
ACE documentation needs a fix?
Hello,
The ACE model matrix spec documentation appears to be incorrect. Minor issue but want to bring to attention:
http://openmx.psyc.virginia.edu/docs/OpenMx/2.3.1/GeneticEpi_Matrix.html#ace-model-a-twin-analysis
The specified model is an ade model (.25%x%C in DZs) but the text refers to ace.
- Read more about ACE documentation needs a fix?
- 2 comments
- Log in or register to post comments
Cindy.s
Joined: 07/04/2015
3 Traits 2 Factors, IP and CP models
Hi OpenMX Community!
I have 3 traits, and I would like to assess whether maybe 2 come from the same genes, while the third has different genes.
That is, I would like to run a IP model with 2 Ac factors, one loading onto 2 traits, and the other one loading onto the last trait. I understand that this would not be identified.
-Is it possible to simplify this by having only 1 Ac factor that loads onto 2 traits, while the last trait only has As factors?
-Would I have to constrain the factor loadings of Ac to be equal since Ac only loads onto two traits?
- Read more about 3 Traits 2 Factors, IP and CP models
- 3 comments
- Log in or register to post comments
Liz
Joined: 04/20/2016
CI estimation of Trivariate Cholesky model
Recently I was trying a trivariate Cholesky model with the latest version of OpenMx. However, when I estimated the standardized CI of parameters, it reported “Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, : NLOPT fatal error -1”. Then I followed the advices of Rob replied to another topic that change the optimizer from “SLSQP” to “NPSOL”. Although it run smoothly, the results contained minus value and bigger than 1 that were very strange, such as:
CholACE.StandardizedA[1,1] 4.835575e-02 0.4772359455 8.043944e-01
- Read more about CI estimation of Trivariate Cholesky model
- 10 comments
- Log in or register to post comments
Jeremy
Joined: 03/25/2016
Twin Correlations for Scalar-Sex Limited Model?
New poster here, and new-ish user to twin analyses. I am trying to run an ACE model that I believe is called "scalar sex limited" -- I want to allow the total variance to differ across sex, but I want to constrain the A, C, and E to be the same so that I am reporting just one heritability estimate. Here are the key parts of my syntax:
twinACEModel <- mxModel("twinACE",
mxModel("ACE",
# ace path coefficients for males and females
mxMatrix("Lower", nrow=nv, ncol=nv, free=TRUE, values=0.2, label="am11", name="am"),
Rolandgem
Joined: 10/24/2015
Analyzing heritability results of a covariate after running the ACE Model
I am studying the heritability of a variable by utilizing the ACE model, and would like to ask the OpenMX community if i am analyzing my results correctly.
When i run the ACE model, followed by the AE and CE models, i get the following results for 2 different datasets:
COMPARE ALL MODELS: Print Comparative Fit Statistics
(Nested.fit <- rbind(
mxCompare(SatFit, AceFit),
mxCompare(AceFit, AEFit)[2,],
mxCompare(AceFit, CEFit)[2,]))
Dataset 1
Model A (95% CI) C (95% CI) E (95% CI) (-2LL) df AIC ∆-2LL ∆df p-value
YiTan
Joined: 10/08/2014
SLSQP error msg in univariate Ordinal ACE with age and sex as covariates
Hi,
I ran the attached ordinal ACE script with age and sex as covariates, and I noticed that for some of my variables I would get the following error message:
"Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, :
SLSQP: Failed due to singular matrix E or C in LSQ subproblem or rank-deficient equality constraint subproblem or positive directional derivative in line search "