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#
# Copyright 2007-2021 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.
# ---------------------------------------------------------------------
# Program: BivariateRaw-OpenMx100214.R
# Author: Steven M. Boker
# Date: Sun Feb 14 13:27:16 EST 2010
#
# This program fits a FIML bivariate model to the
# multiData simulated data.
#
#
# ---------------------------------------------------------------------
# Revision History
# -- Sun Feb 14 13:27:13 EST 2010
# Created BivariateRaw-OpenMx100214.R.
# -- Sun Aug 29 2010
# Formatted for OpenMx Test Suite
# ---------------------------------------------------------------------
# ----------------------------------
# Read libraries and set options.
library(OpenMx)
suppressWarnings(RNGversion("3.5"))
# ----------------------------------
# Read the data and print descriptive statistics.
data(multiData1)
# ----------------------------------
# Build an OpenMx bivariate regression model using y and x1
manifests <- c("x1", "x2", "y")
biRegModelRaw <- mxModel("FIML Bivariate Regression of y on x1 and x2",
type="RAM",
manifestVars=manifests,
mxPath(from=c("x1","x2"), to="y",
arrows=1,
free=TRUE, values=.2, labels=c("b1", "b2")),
mxPath(from=manifests,
arrows=2,
free=TRUE, values=.8,
labels=c("VarX1", "VarX2", "VarE")),
mxPath(from="x1", to="x2",
arrows=2,
free=TRUE, values=.2,
labels=c("CovX1X2")),
mxData(observed=multiData1, type="raw")
)
omxCheckError(mxRun(biRegModelRaw, suppressWarnings=TRUE),
paste("The job for model 'FIML Bivariate Regression of y on x1 and x2' exited abnormally with the error message:",
"MxExpectationRAM: raw data observed but no expected means vector was provided. Add something like mxPath(from = 'one', to = manifests) to your model."))
biRegModelRaw <- mxModel(
biRegModelRaw,
mxPath(from="one", to=manifests,
arrows=1, free=TRUE, values=.1,
labels=c("MeanX1", "MeanX2", "MeanY")))
biRegModelRawOut <- mxRun(biRegModelRaw)
summary(biRegModelRawOut)
omxCheckWarning(summary(biRegModelRawOut, boot.quantile=c(.025,.975)),
"No bootstrap data found. See ?mxBootstrap")
# ----------------------------------
# check for correct values
expectVal <- c(0.4479, 0.4328, 1.1364, 0.5811, 1.5556, 1.412, 0.9849,
1.9741, 2.5529)
expectSE <- c(0.0554, 0.0474, 0.0719, 0.0649, 0.0984, 0.0893, 0.0477, 0.0558,
0.1004)
expectMin <- 4608.207
omxCheckCloseEnough(expectVal, biRegModelRawOut$output$estimate, 0.001)
omxCheckCloseEnough(expectSE,
as.vector(biRegModelRawOut$output[['standardErrors']]), 0.001)
omxCheckCloseEnough(expectMin, biRegModelRawOut$output$minimum, 0.001)
omxCheckCloseEnough(biRegModelRawOut$output$status$code, 0)
omxCheckCloseEnough(biRegModelRawOut$output$iterations, 30, 10)
biRegModelRawBoot <- mxBootstrap(biRegModelRawOut, 10, OK=NULL)
ign <- omxCheckWarning(summary(biRegModelRawBoot),
"Only 0% of the bootstrap replications converged. Accuracy is much less than the 10 replications requested")
set.seed(42)
biRegModelRawBoot <- mxBootstrap(biRegModelRawOut, 10)
omxCheckTrue(is.null(biRegModelRawBoot$output[["standardErrors"]]))
bq1 <- summary(biRegModelRawBoot)[["bootstrapSE"]]
omxCheckCloseEnough(cor(bq1, biRegModelRawOut$output$standardErrors), 1, .16)
biRegModelRawBoot <- mxBootstrap(biRegModelRawBoot)
bq2 <- summary(biRegModelRawBoot)[["bootstrapSE"]]
omxCheckCloseEnough(sum((bq2 - biRegModelRawOut$output$standardErrors)^2), 0, 3.5e-3)
set.seed(42)
biRegModelRawBoot <- mxBootstrap(biRegModelRawBoot, 10)
bq3 <- summary(biRegModelRawBoot)[["bootstrapSE"]]
omxCheckEquals(bq3, bq1)
repl3 <- biRegModelRawBoot$compute$output$raw[3,]
biRegModelRawBoot3 <- mxBootstrap(biRegModelRawBoot, only=3)
omit <- -match('statusCode', colnames(repl3))
omxCheckCloseEnough(repl3[,omit], biRegModelRawBoot3$compute$output$raw[,omit], 1e-6)
# investigate replication 3
biRegModelRaw3 <- mxModel(
biRegModelRaw,
mxData(observed=cbind(multiData1,
freq=biRegModelRawBoot3$compute$output$frequency[[1]]),
type="raw", frequency = "freq"))
biRegModelRaw3 <- mxRun(biRegModelRaw3)
omxCheckCloseEnough(coef(biRegModelRaw3),
unlist(repl3[,names(coef(biRegModelRaw3))]), 1e-5)
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