Behavioral Genetics Models
benruk
Joined: 12/09/2019
Test Moderation of Standardized Variance Components
since in the conventional moderated ACE model proposed by Purcell it is only possible to test whether there is a significant moderation of the unstandardized genetic, shared and unshared variance components in a phenotype, I was wondering whether it is also possible to test if there is a significant moderation of the standardized variance components.
JuanJMV
Joined: 07/20/2016
Modified CP model
I am trying to fit a model (I am not sure if it will be possible) like the one in the attached figure.
I am trying to do it by modifying this script (CP model with one latent factor):
# Fit Common Pathway ACE Model
# ------------------------------------------------------------------------------
nl <- 1
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lior abramson
Joined: 07/21/2017
umxsexlim command-different results in each run for the exact same command
I am trying to conduct a multivariate sex-limitation model. I am not sure why, but when I run the exact same command I get different results in each run (and in some of the runs, the results don't really correspond with the raw data and don't make sense).
I assume that this is the result of an unstable solution. However, I don't get any warning messages that indicate there is anything wrong, or that could direct me what to do.
The script is attached. Do you have an idea what could be the problem?
YiTan
Joined: 10/08/2014
Bivariate ACE model with covariates for ordinal variables
I couldn't find any existing OpenMx codes to conduct bivariate genetic modelling for ordinal variables with covariates, so I've adapted Hermine Mae's twoACEvo.R code (bivariate ACE model for ordinal variables) by adding covariates to the code. I thought it was quite straightforward, but when I ran the code I got the following error:
Error in as.vector(data) :
no method for coercing this S4 class to a vector
YiTan
Joined: 10/08/2014
noamm
Joined: 10/10/2018
George Richardson
Joined: 10/18/2018
Inconsistency between global chi-square difference tests and t-tests
I've specified a multivariate ACE model and found that the z/t-tests produce substantially different p-values than the chi-square difference test per parameter constrained to zero. My recollection is that these tests should produce equivalent results but I recall reading somewhere that at relatively small n (here, n = 260 pairs), the global test may have more power. Does anyone know if this is likely correct or if there are methods papers address it? Could the difference be due to correlations among the z/t-tests? Not sure what's going on here.
JuanJMV
Joined: 07/20/2016
Problem to get the genetic correlations
I have fitted a 4-variate model and I have fixed A to 0 for one of these phenotypes. The model fits OK but I am struggled to obtain the genetic correlations.
This is the output from the model but as one of the A parameters is fixed to 0 I get these results:
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liagym1
Joined: 11/06/2019
ACE with moderator- warning in output
Mx starting optimization; number of parameters = 7
*** WARNING! ***
I am not sure I have found a solution that satisfies
Kuhn-Tucker conditions for a minimum.
NAG's IFAIL parameter is 6
Looks like I got stuck here. Check the following:
1. The model is correctly specified
2. Starting values are good
3. You are not already at the solution
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lemire
Joined: 12/13/2019
Genetic correlation: two ways, two different estimates
I implemented two ways of calculating the genetic correlation between two phenotypes, estimated from twins (direct model of rg between A1 and A2, and Cholesky).
My two implementations are based on the path diagrams from H.H. Maes' slides 18 and 53 found at
https://vipbg.vcu.edu/media/course/HGEN619_2015/BivariateGeneticAnalysis2.pdf
I do not get the same estimates between the two methods (-0.26 vs 0.51). Below is the code with the reproducible fake data and results. The code is also attached.