Behavioral Genetics Models
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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Multivariate ACE-ADE model
I am trying to fit a 5-variate model. But I am not sure about the best way to do it.
I have got these results from the univariate analyses
VAR1
ADE 0.34 0.10 0.57
AE 0.42 * 0.58
VAR2
ADE 0.26 0.16 0.58
AE 0.41 * 0.59
VAR3
ACE 0.29 0.13 0.58
AE 0.45 * 0.55
CE * 0.33 0.67
VAR4
ADE 0.23 0.17 0.59
AE 0.39 * 0.61
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Why mxTryHardOrdinal()dosen't report start values?
When i use
SatFit <- mxTryHardOrdinal(SatModel, intervals=TRUE,extraTries = 15,finetuneGradient=FALSE,bestInitsOutput=TRUE)
,the result is Solution found! Final fit=22505.957 (started at 22819.562) (16 attempt(s): 16 valid, 0 errors)
. I don't know why it dosen't report start values from the best fit.Pagination
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