# # Copyright 2007-2016 The OpenMx Project # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ----------------------------------------------------------------------------- # Program: TwoFactorModel_MatrixRaw.R # Author: Ryne Estabrook # Date: 2009.08.01 # # ModelType: Factor # DataType: Continuous # Field: None # # Purpose: # Two Factor model to estimate factor loadings, residual variances and means # Matrix style model input - Raw data input # # RevisionHistory: # Hermine Maes -- 2009.10.08 updated & reformatted # Ross Gore -- 2011.06.06 added Model, Data & Field metadata # Hermine Maes -- 2014.11.02 piecewise specification # ----------------------------------------------------------------------------- require(OpenMx) # Load Library # ----------------------------------------------------------------------------- data(myFADataRaw) # Prepare Data # ----------------------------------------------------------------------------- manifestVars <- c("x1","x2","x3","y1","y2","y3") latentVars <- c("F1","F2") twoFactorRaw <- myFADataRaw[,manifestVars] dataRaw <- mxData( observed=myFADataRaw, type="raw" ) matrA <- mxMatrix( type="Full", nrow=8, ncol=8, free= c(F,F,F,F,F,F,F,F, F,F,F,F,F,F,T,F, F,F,F,F,F,F,T,F, F,F,F,F,F,F,F,F, F,F,F,F,F,F,F,T, F,F,F,F,F,F,F,T, F,F,F,F,F,F,F,F, F,F,F,F,F,F,F,F), values=c(0,0,0,0,0,0,1,0, 0,0,0,0,0,0,1,0, 0,0,0,0,0,0,1,0, 0,0,0,0,0,0,0,1, 0,0,0,0,0,0,0,1, 0,0,0,0,0,0,0,1, 0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0), labels=c(NA,NA,NA,NA,NA,NA,"l1",NA, NA,NA,NA,NA,NA,NA,"l2",NA, NA,NA,NA,NA,NA,NA,"l3",NA, NA,NA,NA,NA,NA,NA,NA,"l4", NA,NA,NA,NA,NA,NA,NA,"l5", NA,NA,NA,NA,NA,NA,NA,"l6", NA,NA,NA,NA,NA,NA,NA,NA, NA,NA,NA,NA,NA,NA,NA,NA), byrow=TRUE, name="A" ) matrS <- mxMatrix( type="Symm", nrow=8, ncol=8, free= c(T,F,F,F,F,F,F,F, F,T,F,F,F,F,F,F, F,F,T,F,F,F,F,F, F,F,F,T,F,F,F,F, F,F,F,F,T,F,F,F, F,F,F,F,F,T,F,F, F,F,F,F,F,F,T,T, F,F,F,F,F,F,T,T), values=c(1,0,0,0,0,0,0,0, 0,1,0,0,0,0,0,0, 0,0,1,0,0,0,0,0, 0,0,0,1,0,0,0,0, 0,0,0,0,1,0,0,0, 0,0,0,0,0,1,0,0, 0,0,0,0,0,0,1,.5, 0,0,0,0,0,0,.5,1), labels=c("e1",NA, NA, NA, NA, NA, NA, NA, NA, "e2", NA, NA, NA, NA, NA, NA, NA, NA, "e3", NA, NA, NA, NA, NA, NA, NA, NA, "e4", NA, NA, NA, NA, NA, NA, NA, NA, "e5", NA, NA, NA, NA, NA, NA, NA, NA, "e6", NA, NA, NA, NA, NA, NA, NA, NA,"varF1","cov", NA, NA, NA, NA, NA, NA,"cov","varF2"), byrow=TRUE, name="S" ) matrF <- mxMatrix( type="Full", nrow=6, ncol=8, free=FALSE, values=c(1,0,0,0,0,0,0,0, 0,1,0,0,0,0,0,0, 0,0,1,0,0,0,0,0, 0,0,0,1,0,0,0,0, 0,0,0,0,1,0,0,0, 0,0,0,0,0,1,0,0), byrow=TRUE, name="F" ) matrM <- mxMatrix( type="Full", nrow=1, ncol=8, free=c(T,T,T,T,T,T,F,F), values=c(1,1,1,1,1,1,0,0), labels=c("meanx1","meanx2","meanx3", "meanx4","meanx5","meanx6",NA,NA), name="M" ) exp <- mxExpectationRAM("A","S","F","M", dimnames=c(manifestVars, latentVars)) funML <- mxFitFunctionML() twoFactorModel <- mxModel("Two Factor Model Matrix Specification", dataRaw, matrA, matrS, matrF, matrM, exp, funML) # Create an MxModel object # ----------------------------------------------------------------------------- twoFactorFit <- mxRun(twoFactorModel) summary(twoFactorFit) twoFactorFit$output$estimate omxCheckCloseEnough(twoFactorFit$output$estimate[["l2"]], 0.9723, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["l3"]], 0.9313, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["l5"]], 1.0498, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["l6"]], 1.0531, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["varF1"]], 0.6604, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["varF2"]], 0.4505, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["cov"]], 0.2952, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["e1"]], 0.3349, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["e2"]], 0.3985, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["e3"]], 0.4091, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["e4"]], 0.5404, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["e5"]], 0.4809, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["e6"]], 0.5571, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["meanx1"]], 2.988, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["meanx2"]], 3.0113, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["meanx3"]], 2.9861, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["meanx4"]], 2.9554, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["meanx5"]], 2.9562, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["meanx6"]], 2.9673, 0.01) # Compare OpenMx results to Mx results # -----------------------------------------------------------------------------