Nothing
library("JointAI")
if (identical(Sys.getenv("NOT_CRAN"), "true")) {
test_that('Joint model with ordinal covariate works', {
test <- JM_imp(list(Surv(futime, status != 'censored') ~ stage + age + sex,
stage ~ age + sex + day + (day | id)),
data = PBC, timevar = "day",
n.adapt = 3, n.iter = 3, warn = FALSE, seed = 2020,
mess = FALSE)
expect_s3_class(test, class = "JointAI")
})
test_that('JM', {
mod <- JM_imp(list(Surv(futime, status != "censored") ~ age + sex + chol +
stage + hepato + (1 | id),
hepato ~ day + (1 | id),
chol ~ day + (1 | id),
stage ~ age + (1 | id)),
timevar = 'day', data = JointAI::PBC,
warn = FALSE, n.iter = 5, n.adapt = 2)
expect_s3_class(mod, 'JointAI')
expect_output(list_models(mod))
expect_s3_class(parameters(mod), 'data.frame')
expect_s3_class(summary(mod), 'summary.JointAI')
})
test_that("fill_locf works", {
locfdat <- JointAI:::fill_locf(data = JointAI::PBC,
fixed = list(Surv(futime, status != "censored") ~
age + sex + hepato + platelet),
auxvars = NULL,
random = ~ 1 | id, timevar = 'day',
groups = JointAI:::get_groups('id',
JointAI::PBC))
expect_s3_class(locfdat, 'data.frame')
expect_equal(colSums(is.na(locfdat[, c('hepato', 'platelet')])),
c('hepato' = 0, 'platelet' = 0))
})
}
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