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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)
# Multilevel Long Format Test
# Author: Steve Boker
# Date: Sun Nov 29 14:06:07 EST 2009
# This script is used to test the multilevel long format functionality using definition variables
# as indices.
set.seed(42) # repeatibility
tID <- rep(1:10, each=10)
trueX <- rep(rnorm(10, mean=0, sd=2), each=10) + rnorm(100, mean=0, sd=.2)
trueB <- rep(rnorm(10, mean=0, sd=.5), each=10)
tDataFrame <- data.frame(ID=tID, X=trueX, Y=trueB*trueX + rnorm(100, mean=0, sd=.2))
summary(tDataFrame)
manifestVars <- c("X", "Y")
numSubjects <- length(unique(tDataFrame$ID))
RandVals <- matrix(c(.2, 0, 0, .8, .8), numSubjects, 5, byrow=TRUE)
multilevelModel2 <- mxModel("Multilevel_2",
mxMatrix("Full",
values=RandVals,
free=TRUE,
name="Rand"
),
mxMatrix("Full", 2, 2,
labels=c(NA, NA,
"Rand[data.ID,1]", NA),
free=FALSE,
name="A",
byrow=TRUE
),
mxMatrix("Symm", 2, 2,
free=FALSE,
labels=c("Rand[data.ID,4]",
NA, "Rand[data.ID,5]"),
name="S",
byrow=TRUE
),
mxMatrix("Full", 2, 2,
values=c(1,0,
0,1),
free=F, byrow=TRUE, name="F"),
mxMatrix("Iden", 2, name="I"),
mxAlgebra(F %*% solve(I-A) %*% S %*% t(solve(I-A)) %*% t(F),
name="R",
dimnames = list(manifestVars, manifestVars)
),
mxMatrix("Full", nrow=1, ncol=length(manifestVars),
values=0,
free=FALSE,
labels=c("Rand[data.ID,2]", "Rand[data.ID,3]"),
dimnames=list(NULL, manifestVars),
name="M"
),
mxFIMLObjective("R", "M"),
mxData(tDataFrame,
type="raw"
)
)
# ----------------------------------
# Fit the model and examine the summary results.
multilevelModel2Fit <- mxRun(multilevelModel2)
summary(multilevelModel2Fit)
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