Behavioral Genetics Models
JuanJMV
Joined: 07/20/2016
Interpret >1 and negative results from variance parametrisation of twin model
I am using the new parametrization for a bivariate model, as suggested in "Type I Error Rates and Parameter Bias in Multivariate Behavioral Genetic Models".
The results (see below) include an rA correlation that is higher than one.
Am I doing something wrong or I have to interpret the rA correlation as 1?
The phenotypic correlation is .2. Is it be correct to say that is due to 1, -.96 and .2 for A, D and E respectively?
There are also negative values: there is no way to interpret these results, right?
twolf
Joined: 04/24/2020
Should I ever need lower bounds in a twin model?
I am currently starting to familiarize myself with different variations of the ACE-model as well as nuclear twin family designs in OpenMx and although coming from econometrics I dreaded working with SEMs so far I find the ride quite exhilarating.
While trying to reproduce certain results from the literature to broaden my understanding I sometimes encounter a strange behavior where I obtain a parameter estimate which is quite close to what I would expect with the only issue being that it is actually negative.
lior abramson
Joined: 07/21/2017
negative path estimate in UMX cholesky
I conducted a Cholesky model with two variables in two time-points, using the uxACE command, and then conducted a model fitting procedure with the umxModify command. The model was an ADE model.
The results I got (a screenshot is attached) make perfect sense in terms of the overall explained variance by genetics. Meaning, if I compute the variance explained by both A and D for each variable (after squaring each path), I get the same amount of explained genetic variance as in the univariate models for each variable.
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benruk
Joined: 12/09/2019
Covariate Effect in Liability Threshold Model
I want to write a script for a GxE-interaction with an ordinal outcome and a continuous moderator and was looking for some scripts that include a covariate effect on an ordinal outcome variable.
In this search I found a [script](https://static1.squarespace.com/static/58b2481a9f7456906a3b9600/t/5d9c0be7b3de004d53e6456b/1570507752071/oneACEoa.pdf) by Hermine Maes where she models the effect of the covariate (age) on the mean of the liability distribution of the outcome variable.
MIRELA
Joined: 04/03/2020
Biometrical model fitting
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szellers
Joined: 04/04/2018
Cohort Covariate and ACE Estimates
I've been playing around with various ways to include a cohort covariate in a single-factor model. I've tried four approaches, three of which have pretty consistent results and the fourth, which is fairly different. I've attached the four scripts here, as well as a table of selected output (ACE estimates with CIs, factor loadings, and expected means for observed variables).
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lior abramson
Joined: 07/21/2017
best way to (systematically) fit an ADE model
I am trying to fit a longitudinal Cholesky model (two variables in two time-points) with the umxACE and umxModify commands from the umx package.
quino
Joined: 03/12/2020
Mis-specification and model fit interpretation of univariate ACE
I am new to statistical modelling for genetic analysis and after conducting a round of univariate analysis (prior to a future multivariate one) using the umxACE function I have a few questions I would like to ask for help with.
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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