Behavioral Genetics Models
Saturated vs ACE model- different correlations
I am trying to fit a univariate model.
I fitted the saturated model first and I got correlations of 0.64 and 0.34 for MZ and DZ respectively.
However, when I fitted the ACE model, I got these results:
A=0.04
C=0.52
E=0.44
So, I decided to check the correlations from the ACE model and I got 0.56 and 0.54 for MZ and DZ respectively.
I know that correlations may change from the ACE to the saturated model. However, these differences are huge.
what are the meanings of definition variables in SEM in twin studies
For instance, I want to estimate the heritability of smoking( binary variable) and age is added to adjust the threshold.
ACE model with technical replicates
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Failure to obtain CI's for a umx model
I have used umx for a bivariate sex-limitation model, using the umxSexLim function, which have been a great help. However, I've failed in trying to compute CI's for my estimates, or any other indication of significance. Attached below are all the options I've tried. I would appreciate any help in how to compute any indication of significance.
Thanks!
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Modeling Suggestions for Experimental Data
I ran a single-factor survey experiment with a small group of twin respondents (MZs and DZs, mainly same sex). There were two conditions. I randomly assigned twins to receive either:
Conditions A A
Conditions B B
Or
Conditions A B (or B A)
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Age as covariate or moderator
I'm running a set of univariate ACE models, on a range of outcomes. I have two age groups (3-4 and 7-8), that I would like to analyse separately, by also combined.
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Obtain 95%CI for ACE model- script revised from Dorothy Bishop
Thanks!
I am wondering if define variables will decrease E and increase A?
For instance, I want to estimate the heritability of coronary heart disease (CHD), should I adjust all the risk factors of CHD as much as possible, such as smoking, drinking and BMI? I'm afraid that it will overestimate A and underestimate E since I saw a revelent [paper](https://www.ncbi.nlm.nih.gov/pubmed/15520515/).
Many thanks!
About the overlap on the genetic and shared environmental factors
GxE model for binary variable
I want to use the code posted in [there](http://ibg.colorado.edu/cdrom2016/franic/Moderation/Practical/DO_NOT_OPEN_Moderating_covariances_practical_solved.R), but this code is suit for continuous variable and I don't know how to change it to be suit for binary variable. Could you tell me what lines I should change or add?
Because I'm pressed for time, I am sorry to directly ask for solution instead of learning by myself.
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