Behavioral Genetics Models
http://openmx.psyc.virginia.edu/taxonomy/term/23/0
enConceptual Questions on Phenotypic and ACE Cholesky Models
http://openmx.psyc.virginia.edu/thread/2899
<p>Hi all,<br />
I am trying to run both a phenotypic 3 latent factor cholesky and then an ACE Cholesky using the same factor structure and data. My second order F2 and F3 factors are correlated at about .92 and my phenotypic cholesky model runs fine if I allow the error terms of an indicator of F1 and an indicator of F3 to correlate within twin 1 and within twin 2 (to control for shared method variance). However, if I remove the correlations, then the correlation between F3 for twin 1 and F3 for twin 2 exceeds 1.0 and I got a messaging saying that the covariance matrix for these two factors is not positive definite. Thus, my first question is: Am I violating any assumptions of the cholesky models by allowing the error terms across F1 and F3 to correlate? It seems like this method works out well in my case because it somehow removes the multicollinearity issue and the error message goes away. However, I want to make sure that my method is conceptually sound and that it doesn't somehow screw up my ACE estimates. </p>
<p>Another related question is how come all the Fs factors in Cholesky Models usually not allowed to correlate (i.e. no double headed arrows above these factors)? In reality, these factors tend to correlate and in my case, very highly and yet, what I have seen so far (mostly in journal articles and Hermine Maes's power point slides on Multivariate Genetic Analysis) is that these Fs are assumed to be independent. </p>
<p>My third question is does it make a difference that I use both twins' data to conduct phenotypic choleskys vs. just using twin 1 (randomly selected) data? I have tried it both ways and obtained very similar estimates. </p>
<p>Thank you in advance for your insights on this,<br />
Anne</p>
http://openmx.psyc.virginia.edu/thread/2899#commentsBehavioral Genetics ModelsSat, 19 Apr 2014 22:31:04 +0000AnneN.2899 at http://openmx.psyc.virginia.edup-values from correlation estimates in bivariate model
http://openmx.psyc.virginia.edu/thread/2552
<p>Hello, </p>
<p>I was wondering if p-values for estimated genetic correlations can be obtained directly from the model output, in addition to confidence intervals? </p>
<p>I know that a genetic correlation is significant when zero is not included in the CI, but I need a p-value for multiple comparison correction as I will be running many models. </p>
<p>Any help would be much appreciated,</p>
<p>Marc</p>
http://openmx.psyc.virginia.edu/thread/2552#commentsBehavioral Genetics ModelsFri, 10 Jan 2014 10:56:03 +0000mbohlken2552 at http://openmx.psyc.virginia.eduCorrelated Factors Sex limitation model
http://openmx.psyc.virginia.edu/thread/2439
<p>Hello</p>
<p>I downloaded from the OpenMX website the correlated factors sex limitation model, and amended it for our data (removing the opposite sex components as our twins are all same sex).</p>
<p>The script runs and converges but there is no output (seeming that it is not fitting). There are no warning messages and no error messages. The output we get is:</p>
<p>observed statistics: 4500<br />
estimated parameters: 0<br />
degrees of freedom: 4500<br />
-2 log likelihood: NA<br />
saturated -2 log likelihood: NA<br />
number of observations: 750<br />
chi-square: NA<br />
p: NA<br />
AIC (Mx): NA<br />
BIC (Mx): NA<br />
adjusted BIC:<br />
RMSEA: NA<br />
timestamp: 2013-11-15 09:54:40<br />
frontend time: 9.456 secs<br />
backend time: 0.125 secs<br />
independent submodels time: 0 secs<br />
wall clock time: 9.581 secs<br />
cpu time: 9.581 secs<br />
openmx version number: 1.0.7-1706 </p>
<p>A number of us have looked at this, and just can't work out where the glitch is.</p>
<p>The data and script are attached.</p>
<p>Thank you so much for any assistance in advance!</p>
<p>Karen</p>
<table id="attachments" class="sticky-enabled">
<thead><tr><th>Attachment</th><th>Size</th> </tr></thead>
<tbody>
<tr class="odd"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/Sex limitation correlated factors_0.R">Sex limitation correlated factors.R</a></td><td>19.81 KB</td> </tr>
<tr class="even"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/DASS_Data_Dummy_2.csv">DASS_Data_Dummy.csv</a></td><td>47.9 KB</td> </tr>
</tbody>
</table>
http://openmx.psyc.virginia.edu/thread/2439#commentsBehavioral Genetics ModelsThu, 14 Nov 2013 23:03:50 +0000koak2439 at http://openmx.psyc.virginia.eduSEM example on genes scenario
http://openmx.psyc.virginia.edu/thread/2425
<p>Hello,<br />
I wanted to work the following as an example of how to apply SEM in genes scenario<br />
<a href="http://www.biomedcentral.com/1753-6561/1/S1/S76" title="http://www.biomedcentral.com/1753-6561/1/S1/S76">http://www.biomedcentral.com/1753-6561/1/S1/S76</a></p>
<p>or</p>
<p><a href="https://www.google.mu/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CC8QFjAA&url=http%3A%2F%2Fwww8.sas.com%2Fscholars%2FProceedings%2F2006%2FSTAT%2FST06_06.PDF&ei=1xl9UvehHYnwrQec34Ew&usg=AFQjCNFEKotV1T6cZ_sJVS8N1oHYrXwDAg&bvm=bv.56146854,d.bmk" title="https://www.google.mu/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CC8QFjAA&url=http%3A%2F%2Fwww8.sas.com%2Fscholars%2FProceedings%2F2006%2FSTAT%2FST06_06.PDF&ei=1xl9UvehHYnwrQec34Ew&usg=AFQjCNFEKotV1T6cZ_sJVS8N1oHYrXwDAg&bvm=bv.56146854,d.bmk">https://www.google.mu/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&v...</a></p>
<p>But I'm not able to locate the data used for this examples from the link provided in this articles. There several data on SNP, GENE provided by the NCBI(<a href="http://www.ncbi.nlm.nih.gov/" title="http://www.ncbi.nlm.nih.gov/">http://www.ncbi.nlm.nih.gov/</a>) but I don't know which data should be used. And I wanted to know how to enter the genes data into R using any package like openMx to construct the SEM model.</p>
<p>If possible, can you provide me with a complete worked example on any gene scenario where we have to apply Structural Equation Modeling so that I have an idea how I should begin my project with my own data set.</p>
http://openmx.psyc.virginia.edu/thread/2425#commentsBehavioral Genetics ModelsSun, 10 Nov 2013 07:57:35 +0000lekharsha2425 at http://openmx.psyc.virginia.eduAge&Gender Covariates; Continuous data; Multivariate Analysis
http://openmx.psyc.virginia.edu/thread/2395
<p>Hi all, </p>
<p>I would like to covariate for age & gender in a multivariate analysis. I found scripts to covariate but in ordinal data and in univarite analysis. </p>
<p>It would be really helpful for me it any of you could show me an example of a script on how to covariate (by age and gender) in a MV analysis, because I now from my previous univariate analysis that gender could be causing some genetic sex differences in 4 of the 6 traits that I’m using. </p>
<p>Thank you very much!!! </p>
http://openmx.psyc.virginia.edu/thread/2395#commentsBehavioral Genetics ModelsWed, 23 Oct 2013 15:23:25 +0000luna.clara2395 at http://openmx.psyc.virginia.eduMultivariate Analysis: Saturated model with restrictions
http://openmx.psyc.virginia.edu/thread/2394
<p>Hi all,<br />
I’m trying to run a saturated model with restrictions in a multivarite analysis with 6 continuous variables. </p>
<p>In this saturated model with restrictions (see below) I had the following problem (that I did not have in the saturated model without restrictions):<br />
Error: The job for model 'Con' exited abnormally with the error message: Expected covariance matrix is not positive-definite in data row 431 at major iteration 0 (minor iteration 1).</p>
<p>However, when I use the same script but instead of 6 with 5 variables or less, the script runs perfectly. I don’t know what it’s happing… I think it’s something related to the starting values, but I don’t know how I can solve this.</p>
<p>Any help would be very helpful. </p>
<p>Many thanks in advance. </p>
<p>#######################################################################<br />
# Restrictions: means and variances equated across birth-order & zygosity groups;<br />
# One set of Cross-trait cor, symmetric Cross-trait Cross-twin correlations (MZ and DZ)</p>
<p># Create start values<br />
# To avoid starting the optimization at the solution add some random noise<br />
jiggle <-rnorm((nv*(nv+1)/2), mean = 0, sd=.1) #calculo jiggle necesario segun estos tamaños<br />
Stmean <-colMeans(Data,na.rm=TRUE)<br />
Stsd <-sd(Data,na.rm=TRUE)+jiggle[1:nv]<br />
StWithinperson <-vechs(cor(Data,use="complete")) +jiggle[1:(nv*(nv-1)/2)]<br />
StBetweenMZ <-vech(cov(mzData[,1:nv],mzData[,(nv+1):(2*nv)],use="complete")) +jiggle<br />
StBetweenDZ <-vech(cov(dzData[,1:nv],dzData[,(nv+1):(2*nv)],use="complete")) +jiggle</p>
<p># Create Labels for Column and Diagonal Matrices<br />
mLabs <- paste("m",1:nv,sep="")<br />
sdLabs <- paste("sd",1:nv,sep="")</p>
<p># Create Lables for a Correlation Matrix<br />
rphLabs <- paste("r",1:ncor,sep="")</p>
<p># Create Labels for Lower Triangular Matrices<br />
MZbLabs <- paste("mz", do.call(c, sapply(seq(1, nv), function(x){ paste(x:nv, x,sep="") })), sep="")<br />
DZbLabs <- paste("dz", do.call(c, sapply(seq(1, nv), function(x){ paste(x:nv, x,sep="") })), sep="")</p>
<p># Specify Matrices to hold parameter estimates for MZ and DZ data<br />
# elements for one overall Means<br />
meansG <-mxMatrix("Full", 1, ntv, free = TRUE, values = Stmean, labels=c(mLabs,mLabs), name="ExpMeans") </p>
<p># elements for the SD<br />
sdZ <-mxMatrix("Zero", nv, nv, free=F, name="padding")<br />
sdG <-mxMatrix("Diag", nv, nv, free = TRUE, values = Stsd, labels=c(sdLabs), name="SD")<br />
sdT <-mxAlgebra(rbind(cbind(SD,padding), cbind(padding, SD)), name="SDtwin")</p>
<p># elements for the correlations<br />
Rph <-mxMatrix("Stand", nv, nv, free = TRUE, values = StWithinperson, labels=rphLabs, name="within")<br />
MZb <-mxMatrix("Symm", nv, nv, free = TRUE, values = StBetweenMZ, labels=MZbLabs, name="BetweenMZ")<br />
DZb <-mxMatrix("Symm", nv, nv, free = TRUE, values = StBetweenDZ, labels=DZbLabs, name="BetweenDZ")<br />
corMZ <-mxAlgebra(rbind(cbind(within,BetweenMZ), cbind(BetweenMZ, within)), name="RMZ")<br />
corDZ <-mxAlgebra(rbind(cbind(within,BetweenDZ), cbind(BetweenDZ, within)), name="RDZ") </p>
<p># generate expected covariance matrices<br />
covMZ <-mxAlgebra(SDtwin %*% RMZ %*% t(SDtwin), name="ExpCovMZ")<br />
covDZ <-mxAlgebra(SDtwin %*% RDZ %*% t(SDtwin), name="ExpCovDZ")</p>
<p># Data objects for Multiple Groups<br />
dataMZ <- mxData( observed=mzData, type="raw" )<br />
dataDZ <- mxData( observed=dzData, type="raw" )</p>
<p># Objective objects for Multiple Groups<br />
objMZ <- mxFIMLObjective( covariance="ExpCovMZ", means="ExpMeans", dimnames=selVars )<br />
objDZ <- mxFIMLObjective( covariance="ExpCovDZ", means="ExpMeans", dimnames=selVars )</p>
<p># Combine Groups<br />
pars <- list(meansG, sdZ, sdG, sdT, Rph)<br />
modelMZ <- mxModel(pars, MZb, corMZ, covMZ, dataMZ, objMZ, name="MZ" )<br />
modelDZ <- mxModel(pars, DZb, corDZ, covDZ, dataDZ, objDZ, name="DZ" )<br />
minus2ll <- mxAlgebra(expression=MZ.objective + DZ.objective, name="m2LL" )<br />
obj <- mxAlgebraObjective( "m2LL" )<br />
ConCorModel <- mxModel("Con", pars, modelMZ, modelDZ, minus2ll, obj )<br />
ConCorFit <- mxRun(ConCorModel)<br />
ConCorSumm <- summary(ConCorFit)</p>
http://openmx.psyc.virginia.edu/thread/2394#commentsBehavioral Genetics ModelsWed, 23 Oct 2013 15:03:12 +0000luna.clara2394 at http://openmx.psyc.virginia.eduDF Extremes Analysis
http://openmx.psyc.virginia.edu/thread/2384
<p>purcell_Transf&DF.R</p>
<p>Dear OpenMx users,</p>
<p>For those interested in DF analysis, we have written a script which<br />
in part 1 prepares / transforms data as in Purcell's means.gawk and prepare.gawk scripts<br />
and in part 2 runs DF-extremes analysis. </p>
<p>Ref: Maximum likelihood DF-extremes analysis based on Purcell S. & Sham PC, Behav Genet. 2003 May;33(3):271-8.<br />
"A model-fitting implementation of the DeFries-Fulker model for selected twin data".</p>
<p>Please let us know if you have any problems or questions.</p>
<p>Maciej Trzaskowski<br />
Fruhling Rijsdijk</p>
<table id="attachments" class="sticky-enabled">
<thead><tr><th>Attachment</th><th>Size</th> </tr></thead>
<tbody>
<tr class="odd"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/purcell_Transf&DF.R">purcell_Transf&DF.R</a></td><td>11.6 KB</td> </tr>
</tbody>
</table>
http://openmx.psyc.virginia.edu/thread/2384#commentsBehavioral Genetics ModelsWed, 16 Oct 2013 13:39:36 +0000Fruhling2384 at http://openmx.psyc.virginia.eduR3.01 and OpenMx1.3.2
http://openmx.psyc.virginia.edu/thread/2271
<p>Hi,</p>
<p>I'm now using OpenMx to do some heritability analysis, and met a probelm. When installed the OpenMx on R3.01, it indicated that the OpenMx could just be insatalled on R2.15. And then when I installed OpenMx on R2.15, I could not install some packages such as "psych" , which required to be work in R3.01. </p>
<p>Please help me for how could I solve this problem. </p>
<p>Many many thanks.</p>
http://openmx.psyc.virginia.edu/thread/2271#commentsBehavioral Genetics ModelsMon, 12 Aug 2013 14:49:10 +0000margaret2271 at http://openmx.psyc.virginia.eduACE model for extended twin family data.
http://openmx.psyc.virginia.edu/thread/2270
<p>Dear all,</p>
<p>I am trying to add sibling and parents in my heritablity estimation study. But I know little about that. I am wondering do you any example Openmx script of ACE or ADE model which involved not only MZ and DZ but also sibling and parents? If so, could you please send it to me?. Or if you know there is some links or materials which can help me learn by myself, could you also send them to me?<br />
Thank you very much!</p>
http://openmx.psyc.virginia.edu/thread/2270#commentsBehavioral Genetics ModelsMon, 12 Aug 2013 14:17:13 +0000lingsuer872270 at http://openmx.psyc.virginia.eduBest way to deal with outliers in heritability modeling
http://openmx.psyc.virginia.edu/thread/2235
<p>I am wondering if someone can answer a nagging question I have about the best way to deal with outliers in heritability modeling. </p>
<p>It has been suggested to me that using z scores, anyone outside the cut off of +/- 2.5 should have their score altered to be the next extreme score (eg if we have scores of 2.5, 2.9, 3.2 etc these would be 2.5, 2.6, 2.7). I am concerned that this will really alter the heritability results. Any thoughts?</p>
<p>Is is better to just remove any outliers from the analyses?</p>
<p>And, if the latter, is the standard +/- 2.5 standard deviations the best cut off to use or is there a better determination?</p>
<p>Thank you so much</p>
<p>Karen </p>
http://openmx.psyc.virginia.edu/thread/2235#commentsBehavioral Genetics ModelsFri, 26 Jul 2013 05:50:06 +0000koak2235 at http://openmx.psyc.virginia.eduCommon Pathways model with age moderation
http://openmx.psyc.virginia.edu/thread/2225
<p>Hello</p>
<p>I am wondering if it is possible to apply the age moderation script from Boulder (attached) to the Common Pathways model? I have tried to do it but end up with multiple problems (one of which is how to add an age moderation to the f component - but that is almost the least of my worries) - my attempt is also attached. Any help would be greatly appreciated.</p>
<p>Thank you in advance</p>
<p>Karen</p>
<table id="attachments" class="sticky-enabled">
<thead><tr><th>Attachment</th><th>Size</th> </tr></thead>
<tbody>
<tr class="odd"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/ModTwinMaRawCon.R">ModTwinMaRawCon.R</a></td><td>10.52 KB</td> </tr>
<tr class="even"><td><a href="http://openmx.psyc.virginia.edu/sites/default/files/Common Pathways - with age moderator.R">Common Pathways - with age moderator.R</a></td><td>19.27 KB</td> </tr>
</tbody>
</table>
http://openmx.psyc.virginia.edu/thread/2225#commentsBehavioral Genetics ModelsMon, 22 Jul 2013 06:21:58 +0000koak2225 at http://openmx.psyc.virginia.eduViolation of assumption of equal variances MZ and DZ
http://openmx.psyc.virginia.edu/thread/2219
<p>Hello</p>
<p>My data of cognitive measures is indicating a number of violations of the assumptions of the twin model. I have transformed the data using z scores and still find that MZ and DZ variances are different. Any ideas on how I should proceed, including how to adjust the script in the ACE/ADE model to deal with this?</p>
<p>Many thanks</p>
<p>Karen</p>
http://openmx.psyc.virginia.edu/thread/2219#commentsBehavioral Genetics ModelsThu, 18 Jul 2013 23:54:39 +0000koak2219 at http://openmx.psyc.virginia.eduage&sex as covariates; ordinal data
http://openmx.psyc.virginia.edu/thread/2179
<p>This is the first time I use open Mx.<br />
without such covariates, my script runs.</p>
<p>Now, I add age and sex as definition factors. results show :<br />
'Unknown thresholds name 'expThreMZ1' detected in the objective function of model 'MZ'.</p>
<p>I don`t know what is wrong. So if you could give me some help? Thanks.</p>
<p>=================================================<br />
MeanL <-mxMatrix( type="Zero", nrow=1, ncol=ntv, name="M" )</p>
<p>Inc <-mxMatrix( type="Lower", nrow=nth, ncol=nth, free=FALSE, values=1, name="L" )<br />
Tmz <-mxMatrix(type="Full", ........, name="ThMZ" )<br />
ThreMZ<-mxAlgebra( expression= L %*% ThMZ, name="expThreMZ" )</p>
<p>Tdz <-mxMatrix(type="Full", ........., name="ThDZ" )<br />
ThreDZ<-mxAlgebra( expression= L %*% ThDZ, name="expThreDZ" )</p>
<p>CorMZ <-mxMatrix(type="Stand", nrow=ntv, ncol=ntv, free=T, values=.6, lbound=-.99, ubound=.99, name="expCorMZ")<br />
CorDZ <-mxMatrix(type="Stand", nrow=ntv, ncol=ntv, free=T, values=.3, lbound=-.99, ubound=.99, name="expCorDZ") </p>
<p># Data objects for Multiple Groups<br />
dataMZ <- mxData( observed=mzDataF, type="raw" )<br />
dataDZ <- mxData( observed=dzDataF, type="raw" )</p>
<p>#defination var<br />
ageT1MZ <- as.vector(subset(ukdata, zg==1, age1))<br />
ageT2MZ <- as.vector(subset(ukdata, zg==1, age2))<br />
ageT1DZ <- as.vector(subset(ukdata, zg==2, age1))<br />
ageT2DZ <- as.vector(subset(ukdata, zg==2, age2))<br />
sexT1MZ <- as.vector(subset(ukdata, zg==1, sex1))<br />
sexT2MZ <- as.vector(subset(ukdata, zg==1, sex2))<br />
sexT1DZ <- as.vector(subset(ukdata, zg==2, sex1))<br />
sexT2DZ <- as.vector(subset(ukdata, zg==2, sex2))</p>
<p>Co <- mxMatrix( type="Full", nrow=2, ncol=2, free=TRUE, values= 0.1, label=c("betaAge","betaSex"), name="beta")<br />
# Algebra for making the means a function of the definition variables age and sex<br />
DefMZ <- mxMatrix( type="Full", nrow=2, ncol=2, free=F, label=c("data.ageT1MZ","data.sexT1MZ","data.ageT2MZ","data.sexT2MZ"), name="MZDefVars")<br />
DefMZ1 <- mxAlgebra( expression=expThreMZ + beta %*% MZDefVars, name="expThreMZ1")</p>
<p>DefDZ <- mxMatrix( type="Full", nrow=2, ncol=2, free=F, label=c("data.ageT1DZ","data.sexT1DZ","data.ageT2DZ","data.sexT2DZ"), name="DZDefVars")<br />
DefDZ1 <- mxAlgebra( expression=expThreDZ+ beta %*% DZDefVars, name="expThreDZ1")</p>
<p>objMZ <- mxFIMLObjective( covariance="expCorMZ", means="M", dimnames=selVars, thresholds="expThreMZ1" )<br />
objDZ <- mxFIMLObjective( covariance="expCorDZ", means="M", dimnames=selVars, thresholds="expThreDZ1" )</p>
<p># Combine Groups<br />
modelMZ <- mxModel( MeanL, Inc, Tmz, ThreMZ, CorMZ, dataMZ,objMZ, name="MZ" )<br />
modelDZ <- mxModel( MeanL, Inc, Tdz, ThreDZ, CorDZ, dataDZ,objDZ, name="DZ" )<br />
minus2ll <- mxAlgebra( expression=MZ.objective + DZ.objective, name="m2LL" )<br />
obj <- mxAlgebraObjective( "m2LL" )<br />
Conf <- mxCI (c ('MZ.expCorMZ[2,1]', 'DZ.expCorDZ[2,1]') )<br />
SatModel <- mxModel( "Sat", modelMZ, modelDZ, minus2ll, obj, Conf )</p>
<p># -------------------------------------------------------------------------------------------------------------------------------<br />
# 1) RUN Saturated Model</p>
<p>SatFit <- mxRun(SatModel, intervals=T)</p>
http://openmx.psyc.virginia.edu/thread/2179#commentsBehavioral Genetics ModelsThu, 27 Jun 2013 02:33:49 +0000fishfis2179 at http://openmx.psyc.virginia.eduerror in biv model with definition variable
http://openmx.psyc.virginia.edu/thread/2175
<p>Hi,<br />
I am trying to fit a biv model (2 continuous phenotypes) with sex as definition variable to test for mean differences, however I get the same error over and over again:</p>
<p>Error: A definition variable has been declared in model 'Chol' that does not contain a data set</p>
<p>I cannot find where it goes wrong, I suspect it's somewhere in the matrices declared to store linear coefficients for covariate:</p>
<p>grandMean <- mxMatrix(type="Full", nrow=1, ncol=nphen, free = TRUE, values=c(2700, 19), label=c("mean1","mean2"), name="Mean")<br />
B_Sex <- mxMatrix(type="Full", nrow=ndef, ncol=nvar, free=TRUE, values=c(900,2.7), label=(rep(c("bphen1","bphen2"), 2)), name="bSex" )<br />
defSex <- mxMatrix(type="Full", nrow=ndef, ncol=nvar, free=FALSE, labels=(rep(c("data.Sex1","data.Sex2"),each=2)), name="Sex")<br />
SexR <- mxAlgebra(bSex * Sex, name="SexR")<br />
expMean <- mxAlgebra(name="expMean", expression= cbind(Mean, Mean) + SexR)</p>
<p>Any help would be very much appreciated!</p>
<p>Regards,<br />
Nienke</p>
http://openmx.psyc.virginia.edu/thread/2175#commentsBehavioral Genetics ModelsMon, 24 Jun 2013 08:38:58 +0000Nienke2175 at http://openmx.psyc.virginia.eduNew genes and genetic amplification
http://openmx.psyc.virginia.edu/thread/2100
<p>Hi,<br />
I am quietly new to Openmx and thankful for any help that I can get.<br />
I have repeated measurement of continuous variable over two time periods to which I would to do similar analysis as in the De Geus et al (2007) : Bivariate Genetic Modeling of Cardiovascular Stress Reactivity: Does Stress Uncover Genetic Variance?.<br />
I am starting from the script (<a href="http://www.vipbg.vcu.edu/vipbg/HGEN619/BivTwinMaRawCon.R" title="http://www.vipbg.vcu.edu/vipbg/HGEN619/BivTwinMaRawCon.R">http://www.vipbg.vcu.edu/vipbg/HGEN619/BivTwinMaRawCon.R</a>) of bivariate cholesky by Hermine Maes. What I would to do is to add a test of genetic amplification (a11=a21?) as well as whether there is a new gene that comes into play later stage in life (a22=0?). </p>
<p>Thankful for any help to formulate this new addition to the model!</p>
http://openmx.psyc.virginia.edu/thread/2100#commentsBehavioral Genetics ModelsTue, 07 May 2013 19:39:03 +0000Ahmed2100 at http://openmx.psyc.virginia.edu