# # 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_PathRaw.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 # Path 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 # ----------------------------------------------------------------------------- twoFactorRaw <- myFADataRaw[,c("x1","x2","x3","y1","y2","y3")] dataRaw <- mxData( observed=twoFactorRaw, type="raw" ) # residual variances resVars <- mxPath( from=c("x1", "x2", "x3", "y1", "y2", "y3"), arrows=2, free=TRUE, values=c(1,1,1,1,1,1), labels=c("e1","e2","e3","e4","e5","e6") ) # latent variances and covariance latVars <- mxPath( from=c("F1","F2"), arrows=2, connect="unique.pairs", free=TRUE, values=c(1,.5,1), labels=c("varF1","cov","varF2") ) # factor loadings for x variables facLoadsX <- mxPath( from="F1", to=c("x1","x2","x3"), arrows=1, free=c(F,T,T), values=c(1,1,1), labels=c("l1","l2","l3") ) # factor loadings for y variables facLoadsY <- mxPath( from="F2", to=c("y1","y2","y3"), arrows=1, free=c(F,T,T), values=c(1,1,1), labels=c("l4","l5","l6") ) # means means <- mxPath( from="one", to=c("x1","x2","x3","y1","y2","y3","F1","F2"), arrows=1, 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", "meany1","meany2","meany3",NA,NA) ) twoFactorModel <- mxModel("Two Factor Model Path Specification", type="RAM", manifestVars=c("x1", "x2", "x3", "y1", "y2", "y3"), latentVars=c("F1","F2"), dataRaw, resVars, latVars, facLoadsX, facLoadsY, means) # 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[["meany1"]], 2.9554, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["meany2"]], 2.9562, 0.01) omxCheckCloseEnough(twoFactorFit$output$estimate[["meany3"]], 2.9673, 0.01) # Compare OpenMx results to Mx results # -----------------------------------------------------------------------------