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#
# Copyright 2007-2019 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)
data(myLongitudinalData)
# Prepare Data
# -----------------------------------------------------------------------------
dataRaw <- mxData( observed=myLongitudinalData, type="raw" )
# residual variances
resVars <- 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
latVars <- mxPath( from=c("intercept","slope"), arrows=2, connect="unique.pairs",
free=TRUE, values=c(1,1,1), labels=c("vari","cov","vars") )
# intercept loadings
intLoads <- mxPath( from="intercept", to=c("x1","x2","x3","x4","x5"), arrows=1,
free=FALSE, values=c(1,1,1,1,1) )
# slope loadings
sloLoads <- mxPath( from="slope", to=c("x1","x2","x3","x4","x5"), arrows=1,
free=FALSE, values=c(0,1,2,3,4) )
# manifest means
manMeans <- mxPath( from="one", to=c("x1","x2","x3","x4","x5"), arrows=1,
free=FALSE, values=c(0,0,0,0,0) )
# latent means
latMeans <- mxPath( from="one", to=c("intercept", "slope"), arrows=1,
free=TRUE, values=c(1,1), labels=c("meani","means") )
growthCurveModel <- mxModel("Linear Growth Curve Model Path Specification",
type="RAM",
manifestVars=c("x1","x2","x3","x4","x5"),
latentVars=c("intercept","slope"),
dataRaw, resVars, latVars, intLoads, sloLoads,
manMeans, latMeans)
#Create an MxModel object
# -----------------------------------------------------------------------------
growthCurveFit <- mxRun(growthCurveModel, suppressWarnings=TRUE)
mxStandardizeRAMpaths(growthCurveFit,T)
rg <- imxRowGradients(growthCurveFit)
rcov <- OpenMx::"%&%"(solve(growthCurveFit$output$hessian/2), nrow(rg)*var(rg/-2))
mxStandardizeRAMpaths(growthCurveFit,SE=T,cov=rcov)
#Check warnings and errors:
pointlessConstraint <- mxModel(growthCurveFit, mxConstraint(1==1))
pointlessConstraint <- mxRun(pointlessConstraint)
# omxCheckWarning(
# mxStandardizeRAMpaths(pointlessConstraint, T, rcov),
# "standard errors may be invalid because model 'Linear Growth Curve Model Path Specification' contains at least one mxConstraint"
# )
anAlg <- mxAlgebra(1+1)
omxCheckError(
mxStandardizeRAMpaths(growthCurveFit,T,anAlg),
"non-NULL value to argument 'cov' must be (or be coercible to) a matrix"
)
omxCheckError(
mxStandardizeRAMpaths(growthCurveFit,T,matrix(1:6,nrow=2)),
"non-NULL value to argument 'cov' must be a square matrix; it has 2 rows and 3 columns"
)
rcov2 <- rcov
rownames(rcov2) <- NULL
omxCheckError(
mxStandardizeRAMpaths(growthCurveFit, T, rcov2),
"non-NULL value to argument 'cov' must have matching and complete rownames and colnames"
)
omxCheckError(
mxStandardizeRAMpaths(growthCurveFit, T, rcov[-1,-1]),
"value of argument 'cov' has dimension 5, but 'Linear Growth Curve Model Path Specification' has 6 free parameters"
)
rcov3 <- rcov
colnames(rcov3) <- c("res","vari","cov","vars","meani","means")
rownames(rcov3) <- c("res","vari","cov","vars","meani","means")
omxCheckError(
mxStandardizeRAMpaths(growthCurveFit, T, rcov3),
"the dimnames of the matrix provided for argument 'cov' do not match the free-parameter labels of 'Linear Growth Curve Model Path Specification'"
)
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