# SCRIPT: NTF_design.R - NTF design in OpenMx # Author: Matt Keller & Sarah Medland; edited by Tim Bates # History: Thu Sep 24 17:23:33 BST 2009 # 2017-04-14 04:15PM Updated by tbates to use multifgroup. but this code seem to have a bug (missing ALL object), # and did not check the run model, but rather the un-run model... # For description of model, see Keller, Medland, Duncan, Hatemi, Neale, Maes, & Eaves (2009) TRHG, 21, p.8 - 18. # 2009-09-24: (tb): Use three groups (change MZ and DZ family algebra so that they refer to a common set of matrices in a new "NTF" group); # 2009-09-24: (tb): Simplify/speed algebra using Quadratic operator and pre-calculating variance components i.e., e %*% t(e) = E etc; # Mon Sep 28 22:12:31 BST 2009: (tb) read data from DEMO folder # Rhelp: http://www.statmethods.net # OpenMx: http://www.openmx.virginia.com ########################################## require(OpenMx); # TODO: Add output from old MZ to verify correctness # TODO: Verify algebra/constraint specification #NOTE: the minor difference between simulated & estimated parameters are to be expected & are due to sampling error # > res.mat # Var.E Var.F Var.A Var.S Var.D Cor.Sps Var.Phen #OpenMx-Estimated 0.443 0.100 0.294 0.149 0 0.209 0.986 #Old.mx 0.442 0.099 0.294 0.149 0 0.206 0.986 #Simulated 0.433 0.100 0.304 0.197 0 0.200 1.032 #Get Data data(nuclear_twin_design_data) selVars <-names(nuclear_twin_design_data)[1:4] mzData <- nuclear_twin_design_data[nuclear_twin_design_data$zyg=='mz',selVars] dzData <- nuclear_twin_design_data[nuclear_twin_design_data$zyg=='dz',selVars] #Fit NTF Model with RawData and Matrices Input ntf <- mxModel(model="NTF", # Matrices # NOTE: NTF design does not allow Vs & Vf to be estimated simultaneously; for identifiability, choose either m or s to be free and the other to be fixed at 0 #mxMatrix(type="Full", nrow=1, ncol=1, free=FALSE, values=0, label="FamilialPath", name="m"), #fix m=0 if you want Vf=0 #mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=.3, label="Sib", name="s"), #fix s=0 if you want Vs=0 mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=.3, label="FamilialPath", name="m"), #fix m=0 if you want Vf=0 mxMatrix(type="Full", nrow=1, ncol=1, free=FALSE, values=0, label="Sib", name="s"), #fix s=0 if you want Vs=0 mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=.7, label="Env", name="e"), mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=.6, label="AddGen", name="a"), mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=.2, label="Dominance", name="d"), mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=.1, label="AMCopath", name="mu"), mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=1.2, label="VarPhen", name="Vp1"), mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=.2, label="VarF", name="x1"), #keep this parameter free, even if Vf is fixed to 0 mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=.25, label="CovPhenGen", name="delta1"), mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=1, label="VarAddGen", name="q1"), mxMatrix(type="Full", nrow=1, ncol=1, free=TRUE, values=.15, label="CovFA", name="w1"), #mxAlgebra section - nonlinear constraints mxAlgebra(e %*% t(e), name="E"), mxAlgebra(d %*% t(d), name="D"), mxAlgebra(s %*% t(s), name="S"), mxAlgebra((a %&% q1) + x1 + 2 %x% a %*% w1 + E + D + S, name="Vp2"), mxAlgebra(2 %x% m %&% Vp1 + 2 %x% (m %&% (mu %&% Vp1)), name="x2"), mxAlgebra(q1 %*% a + w1, name="delta2"), mxAlgebra(1 + delta1 %*% mu %*% t(delta1), name="q2"), mxAlgebra(delta1 %*% m + delta1 %*% mu %*% Vp1 %*% t(m), name="w2"), #constraints - equating nonlinear constraints and parameters mxConstraint(Vp1 == Vp2, name='VpCon'), mxConstraint(x1 == x2, name='xCon'), mxConstraint(delta1 == delta2,name='deltaCon'), mxConstraint(q1 == q2, name='qCon'), mxConstraint(w1 == w2, name='wCon'), #mxAlgebra section - relative covariances mxAlgebra(a %&% q1 + x1 + 2 %x% a %*% w1 + D + S, name="CvMz"), mxAlgebra(a %&% (q1-.5) + .25 %x% d %*% t(d) + x1 + 2 %x% a %*% w1 + S, name="CvDz"), mxAlgebra(.5 %x% a %*% (q1 %*% a + w1) + .5 %x% a %*% (q1 %*% a + w1) %*% mu %*% Vp1 + m %*% Vp1 + m %*% Vp1 %&% mu, name="ParChild"), mxAlgebra(Vp1 %&% mu, name="CvSps") ) mzModel <- mxModel(name = "MZNTF", mxMatrix(type="Full", nrow=1, ncol=4, free=TRUE, values= .25, label="mean", dimnames=list(NULL, selVars), name="expMeanMz"), # Algebra for expected variance/covariance matrix in MZF mxAlgebra(expression=rbind( cbind(NTF.Vp1, NTF.CvMz, NTF.ParChild, NTF.ParChild), cbind(NTF.CvMz, NTF.Vp1, NTF.ParChild, NTF.ParChild), cbind(NTF.ParChild, NTF.ParChild, NTF.Vp1, NTF.CvSps), cbind(NTF.ParChild, NTF.ParChild, NTF.CvSps, NTF.Vp1) ), dimnames=list(selVars,selVars),name="expCovMz"), mxData(mzData, type="raw"), mxFIMLObjective(covariance="expCovMz",means="expMeanMz") ) dzModel <- mxModel(name = "DZNTF", mxMatrix(type="Full", nrow=1, ncol=4, free=TRUE, values= .25, label="mean", dimnames=list(NULL, selVars), name="expMeanDz"), # Algebra for expected variance/covariance matrix in DZF mxAlgebra(expression=rbind( cbind(NTF.Vp1, NTF.CvDz, NTF.ParChild, NTF.ParChild), cbind(NTF.CvDz, NTF.Vp1, NTF.ParChild, NTF.ParChild), cbind(NTF.ParChild, NTF.ParChild, NTF.Vp1, NTF.CvSps), cbind(NTF.ParChild, NTF.ParChild, NTF.CvSps, NTF.Vp1) ), dimnames=list(selVars,selVars),name="expCovDz"), mxData(dzData, type="raw"), mxFIMLObjective(covariance="expCovDz",means="expMeanDz") ) model <- mxModel(model="NucTwFam", mzModel, dzModel, ntf, mxFitFunctionMultigroup(c("MZNTF", "DZNTF")) ) #Run MX fit <- mxRun(model) #Look at results summary(fit) res <- model$output$estimate round(res,3) #compare to simulation # ============================================================ # = The ALL object doesn't appear to exist in this script... = # ============================================================ res.mat <- rbind(round(c(res[1:5]^2,res[6:7]),3), round(ALL$track.changes[c('var.U','var.F','var.A','var.S','var.D','cor.spouses','var.cur.phenotype'),'data.t1'],3)) dimnames(res.mat) <- list(c('OpenMx-Estimated','Simulated'),c('Var.E','Var.F','Var.A','Var.S','Var.D','Cor.Sps','Var.Phen')) # look at implied Covariances round(fit$output$algebras$MZNTF.expCovMz, 3) round(fit$output$algebras$DZNTF.expCovDz, 3)