Behavioral Genetics Models
Questions about biometric LGC
I'm performing biometric latent growth curve analysis with OpenMx and there a few open questions which I hope some of you might know the answer to. I have three cohorts of twins which are each surveyed three times and I am doing separate analysis of every cohort. Variation of age within cohort and wave (survey time point) is small, so I decided to feed waves into the model rather than ages (so the manifests are, phenotypes at t1, phenotype at t2 and phenotype at t3) which leads to my first question
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Two or more environmental mediators in one model
Decomposed ACE variances...now trying to run regressions
I used this [genetic epi path specification annotated guide] (https://vipbg.vcu.edu/vipbg/OpenMx2/docs//OpenMx/latest/GeneticEpi_Path.html#ace-model-a-twin-analysis) to decompose the variances of ACE on a given phenotype (my DV).
Now, though, I need to run a regression and I can't figure out how to feed the ACE variances from above into the regressions. I assume I have to constrain the parameters somehow?
OpenMx Scripts for Gene-Environment correlation (rGE)
I currently need to examine the correlation between additive gene (A) and moderators (such as SES and home language exposure). However, I don't have the OpenMx scripts to conduct rGE (gene-moderator correlation). Can anyone here provide me with an example script of rGE or tell me where I can find such scripts? I would be grateful very much!
ACE, ADE or ACDE model
I saw papers in which they estimated ADE instead of ACE because the correlation between MZs was twice as big as the one for DZs.
So far in my analysis I used the ACE model, and I was wondering whether I should try the ACE one.
I also read of some analysis estimating ACDE model, is there any example twin I could look at?
Is the ACDE analysis impossible when twins are raised together?
Thank you very much for your help
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Latent growth curve modeling
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Correlate residuals in common pathway model
I have fitted a common pathway model—one latent factor and 7 observed variables.
I have fitted a single-factor common pathway model since the previous literature has suggested this structure and also my confirmatory factor analysis.
As previous publications did in the confirmatory factor analysis, the model improved by correlating the residuals between two subscales since these two components have strong component overlap (one sub-scale is used to calculate the other). My confirmatory factor analysis also improved by doing so.
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