Nothing
context('generateLongData')
rngReset()
test_that('generateLongData without fixed and random effects', {
dt = generateLongData(
sizes=c(1, 2),
fixed=Value ~ 0,
cluster=~1,
random=~0,
id='Id',
data=data.frame(Time=c(0,1)),
fixedCoefs=NULL,
clusterCoefs=cbind(1,2),
randomScales=NULL
)
expect_is(dt, 'data.frame')
expect_equal(nrow(dt), 6)
expect_true(all(dt$Mu.fixed == 0))
expect_equal(dt$Mu.class, rep(1:2, c(2, 4)))
expect_equal(dt$Mu, rep(1:2, c(2, 4)))
expect_false(has_name(dt, 'Mu.random'))
})
test_that('generateLongData with fixed effects', {
dt = generateLongData(
sizes=c(1, 1),
fixed=Value ~ Time,
cluster=~1,
random=~0,
id='Id',
data=data.frame(Time=c(0,.5,1)),
fixedCoefs=c(1,2),
clusterCoefs=cbind(1,2),
randomScales=NULL
)
expect_is(dt, 'data.frame')
expect_length(dt, 7)
expect_equal(nrow(dt), 6)
expect_equal(dt$Mu.fixed, rep(1:3, 2))
expect_equal(dt$Mu.class, rep(1:2, each=3))
expect_equal(dt$Mu, c(2:4, 3:5))
expect_false(has_name(dt, 'Mu.random'))
})
test_that('generateLongData with random intercept', {
set.seed(1)
dt = generateLongData(
sizes=c(10, 10),
fixed=Value ~ Time,
cluster=~1,
random=~1,
id='Id',
data=data.frame(Time=c(0,.5,1)),
fixedCoefs=c(1,2),
clusterCoefs=cbind(1,2),
randomScales=cbind(.1,10)
)
expect_true(has_name(dt, 'Mu.random'))
expect_equal(dt[Time == 0, round(log10(sd(Mu))), by=Class]$V1, c(-1, 1))
})
test_that('generateLongData with scalar random scale', {
set.seed(1)
dt = generateLongData(
sizes=c(10, 10),
fixed=Value ~ Time,
cluster=~1,
random=~1,
id='Id',
data=data.frame(Time=c(0,.5,1)),
fixedCoefs=c(1,2),
clusterCoefs=cbind(1,2),
randomScales=.1
)
expect_true(has_name(dt, 'Mu.random'))
expect_equal(dt[Time == 0, round(log10(sd(Mu))), by=Class]$V1, c(-1, -1))
})
test_that('generateLongData with multiple terms', {
set.seed(1)
dt = generateLongData(
sizes=c(1, 1),
fixed=Value ~ poly(Time, 2, raw=TRUE),
cluster=~poly(Time, 2, raw=TRUE),
random=~poly(Time, 2, raw=TRUE),
id='Id',
data=data.frame(Time=c(0,.5,1)),
fixedCoefs=c(1,2,3),
clusterCoefs=cbind(c(1,1,1),c(2,2,2)),
randomScales=cbind(c(.1,1,2), c(10,1,1))
)
expect_equal(nrow(dt), 6)
expect_length(dt, 10)
expect_equal(dt$Mu.class, c(1, 1.75, 3, 2, 3.5, 6))
})
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