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#
# Copyright 2007-2018 by the individuals mentioned in the source code history
#
# 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.
require(OpenMx)
myLongitudinalDataCov<-matrix(
c(6.362, 4.344, 4.915, 5.045, 5.966,
4.344, 7.241, 5.825, 6.181, 7.252,
4.915, 5.825, 9.348, 7.727, 8.968,
5.045, 6.181, 7.727, 10.821, 10.135,
5.966, 7.252, 8.968, 10.135, 14.220),
nrow=5,
dimnames=list(
c("x1","x2","x3","x4","x5"),c("x1","x2","x3","x4","x5"))
)
myLongitudinalDataMean <- c(9.864, 11.812, 13.612, 15.317, 17.178)
names(myLongitudinalDataMean) <- c("x1","x2","x3","x4","x5")
growthCurveModel <- mxModel("Linear Growth Curve Model, Path Specification",
type="RAM",
mxData(myLongitudinalDataCov,
type="cov",
numObs=500,
means=myLongitudinalDataMean),
manifestVars=c("x1","x2","x3","x4","x5"),
latentVars=c("intercept","slope"),
# residual variances
mxPath(from=c("x1","x2","x3","x4","x5"),
arrows=2,
free=TRUE,
values = c(1, 1, 1, 1, 1),
labels=c("residual","residual","residual","residual","residual")),
# latent variances and covariance
mxPath(from=c("intercept","slope"),
arrows=2,
connect="unique.pairs",
free=TRUE,
values=c(1, 1, 1),
labels=c("vari", "cov", "vars")),
# intercept loadings
mxPath(from="intercept",
to=c("x1","x2","x3","x4","x5"),
arrows=1,
free=FALSE,
values=c(1, 1, 1, 1, 1)),
# slope loadings
mxPath(from="slope",
to=c("x1","x2","x3","x4","x5"),
arrows=1,
free=FALSE,
values=c(0, 1, 2, 3, 4)),
# manifest means
mxPath(from="one",
to=c("x1", "x2", "x3", "x4", "x5"),
arrows=1,
free=FALSE,
values=c(0, 0, 0, 0, 0)),
# latent means
mxPath(from="one",
to=c("intercept", "slope"),
arrows=1,
free=TRUE,
values=c(1, 1),
labels=c("meani", "means"))
) # close model
growthCurveFit<-mxRun(growthCurveModel)
omxCheckCloseEnough(growthCurveFit$output$estimate[["meani"]], 9.930, 0.01)
omxCheckCloseEnough(growthCurveFit$output$estimate[["means"]], 1.813, 0.01)
omxCheckCloseEnough(growthCurveFit$output$estimate[["vari"]], 3.886, 0.01)
omxCheckCloseEnough(growthCurveFit$output$estimate[["vars"]], 0.258, 0.01)
omxCheckCloseEnough(growthCurveFit$output$estimate[["cov"]], 0.460, 0.01)
omxCheckCloseEnough(growthCurveFit$output$estimate[["residual"]], 2.316, 0.01)
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