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# MPLUS: TWO-LEVEL REGRESSION ANALYSIS FOR A CONTINUOUS DEPENDENT VARIABLE WITH A RANDOM INTERCEPT
# https://www.statmodel.com/usersguide/chapter9.shtml
library(OpenMx)
options(width=120)
ex91 <- suppressWarnings(try(read.table("models/nightly/data/ex9.1a.dat")))
if (is(ex91, "try-error")) ex91 <- read.table("data/ex9.1a.dat")
colnames(ex91) <- c('y', 'x', 'w', 'xm', 'clus')
ex91$clus <- as.integer(ex91$clus)
betweenModel <- mxModel(
'betweenModel', type='RAM',
latentVars=c('w', 'xm', 'y'),
mxData(ex91[!duplicated(ex91$clus),], 'raw', primaryKey='clus'),
mxPath('y', arrows=2),
mxPath('one', 'w', free=FALSE, labels='data.w'),
mxPath('one', 'xm', free=FALSE, labels='data.xm'),
mxPath(c('w', 'xm'), 'y'))
withinModel <- mxModel(
'withinModel', type='RAM', betweenModel,
mxData(ex91, 'raw'),
manifestVars='y', latentVars=c('x'),
mxPath('one', 'x', free=FALSE, labels='data.x'),
mxPath('x', 'y'),
mxPath('one', 'y'),
mxPath('y', arrows=2, values=1),
mxPath('betweenModel.y', 'y', free=FALSE, values=1, joinKey='clus'))
withinModel <- mxRun(withinModel)
omxCheckEquals(withinModel$expectation$debug$rampartUsage, 890)
omxCheckCloseEnough(summary(withinModel)$informationCriteria['AIC:','par'], 3063.876, 1e-3)
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