OpenSEM Forums

Negative Genetic Correlation and Positive Shared Environmental Correlation?
I recently ran a bivariate cholesky script in OpenMX and am attempting to write up my results.
The results were a bit odd - I found that the genetic correlation was negative while the shared environmental correlation was positive. The phenotypic correlation is positive. If I am understanding correctly, this means that common genetic influences that serve to increase one trait will decrease the other trait, whereas the common shared environmental influences increase both traits.


some doubts
Hi everyone,
I am really new in OpenMx. I am trying to do a bivariate analysis (dicotomic-quantitative) and I have some questions.
1-I would like to know if I should do a univariate analysis previously I mean in the bivariate analysis The best fitting model could be AE for example, for two variables but in the univariate I could have AE model for one variable and ACE model for the other variable.
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Testing for heterogeneity of total variances of MZ and DZ pairs
I'm analyzing data from a twin study and wondered if OpenMx can test for the assumption that total variances of MZ and DZ pairs are not significantly different. Any suggestion on how to perform this test would be much appreciated!

Constrain the total variance as 1?
Hi,
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Error in Obtaining Cis
I am running a multivariate model (3 dependent vars) with sex (female MZ, male MZ, female DZ, male DZ, F&M DZ, M&F DZ) the model runs fine with the SLSQP optimizer.
No SEs are suspect and the return code is zero.
However when I try the command:
FitCholMod <- mxRun(CholMod, intervals =TRUE)
It runs as before but I receive this error message.
Error in runHelper(model, frontendStart, intervals, silent, suppressWarnings, :
NLOPT fatal error -1
So the confidence intervals are not produced.
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ACE or ADE and results interpretation
Hi,
I'm wondering that in which condition we should choose ACE model, or ADE? Is there any criteria to be referred to? For example, in one trait of my own data, the ACE model indicate the CE model is the best fitted model, while the ADE model indicate the DE model is the best fitted model, is this trait heritable? And in the ADE model, how to calculate the heritability? Only the part of A, or the part of A and D, or only the D?
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CI estimation of standardized path coefficients in common path way model
Hi there,
Now I have a problem about CI estimation in a common pathway model. I can not estimate the CI of the path coeffcients of latent factors. I added following codes to the script:
matIl <- mxMatrix( type="Iden", nrow=nf, ncol=nf, name="Il")
invSDl <- mxAlgebra( expression=solve(sqrt(Il*V)), name="iSDl")
sta <- mxAlgebra(iSDl %*% al, name="sta") # standarized path coefficients of A
stc <- mxAlgebra(iSDl %*% cl, name="stc") # standarized path coefficients of C
ste <- mxAlgebra(iSDl %*% el, name="ste") # standarized path coefficients of E

Need Help about Bivariate ACE model script
Hello, everyone.
I'm new to behavioral genetics. I've learn some knowledge about this area by myself and finish the univariate genetic analysis about twin data. But it's a little difficult for me to find updated bivariate model script. The newest one I found is written on 2012, some lines cannot be read neither by R or me.
I wish someone can throw a web which contain updated bivariate genetic model script.
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ACE estimates do not match twin correlations
Hi all,
I am trying to run a bivariate ACE model. My cross-twin-cross trait correlations are as following:
MZM -.36 (-.44 , -.27) DZM -.23(-.25 ,-.09) DOS -.14(-.21, -.07)
MZF -.24 (-.33, -.14) DZF -.16(-.28 , -.04)
My standardized estimates, however, do not seem to match these correlations. Namely, C is estimated much lower than expected based on the twin correlations (esp. for females).
Males A 0.60(0.38, 0.81) C 0.25(0.07, 0.43) E 0.16(0.14, 0.19)
Females A 0.82(0.48, 1.15) C 0.01 (-.30, 0.30) E 0.18(0.10, 0.27)
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