Nothing
library("JointAI")
# Sys.setenv(IS_CHECK = "true")
skip_on_cran()
PBC2 <- PBC[match(unique(PBC$id), PBC$id), ]
PBC2$center <- cut(as.numeric(PBC2$id), c(-Inf, seq(30, 270, 30), Inf))
PBC$center <- cut(as.numeric(PBC$id), c(-Inf, seq(30, 270, 30), Inf))
PBC2$futime2 <- PBC2$futime
PBC2$status2 <- PBC2$status
PBC2$futime2[1:10] <- NA
PBC2$status2[11:20] <- NA
run_survreg_models <- function() {
sink(tempfile())
on.exit(sink())
invisible(force(suppressWarnings({
models <- list(
# no covariates
m0a = survreg_imp(Surv(futime, status != "censored") ~ 1, data = PBC2,
n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE),
# only complete
m1a = survreg_imp(Surv(futime, status != "censored") ~ age + sex,
data = PBC2, n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE),
m1b = survreg_imp(Surv(futime, I(status != "censored")) ~ age + sex,
data = PBC2, n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE),
# only incomplete
m2a = survreg_imp(Surv(futime, status != "censored") ~ copper, data = PBC2,
n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE),
# complex structures
m3a = survreg_imp(Surv(futime, status != "censored") ~ copper + sex + age +
abs(age - copper) + log(trig),
data = PBC2, trunc = list(trig = c(0.0001, NA)),
n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE),
m3b = survreg_imp(Surv(futime, status != "censored") ~ copper + sex + age +
abs(age - copper) + log(trig) + (1 | center),
data = PBC2, trunc = list(trig = c(0.0001, NA)),
n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE)
)
}
)
))
models
}
models <- run_survreg_models()
models0 <- set0_list(models)
test_that("models run", {
for (k in seq_along(models)) {
expect_s3_class(models[[k]], "JointAI")
}
})
test_that("there are no duplicate betas/alphas in the jagsmodel", {
expect_null(unlist(lapply(models, find_dupl_parms)))
})
test_that("MCMC is mcmc.list", {
for (i in seq_along(models)) {
expect_s3_class(models[[i]]$MCMC, "mcmc.list")
}
})
test_that("MCMC samples can be plottet", {
for (k in seq_along(models)) {
expect_silent(traceplot(models[[k]]))
expect_silent(densplot(models[[k]]))
expect_silent(plot(MC_error(models[[k]])))
}
})
test_that("data_list remains the same", {
expect_snapshot(lapply(models, "[[", "data_list"))
})
test_that("jagsmodel remains the same", {
expect_snapshot(lapply(models, "[[", "jagsmodel"))
})
test_that("GRcrit and MCerror give same result", {
expect_snapshot(lapply(models0, GR_crit, multivariate = FALSE))
expect_snapshot(lapply(models0, MC_error))
})
test_that("summary output remained the same", {
expect_snapshot(lapply(models0, print))
expect_snapshot(lapply(models0, coef))
expect_snapshot(lapply(models0, confint))
expect_snapshot(lapply(models0, summary))
expect_snapshot(lapply(models0, function(x) coef(summary(x))))
})
test_that("prediction works", {
expect_warning(
expect_warning(
predict(models$m3b, type = "lp")$fitted,
"Prediction in multi-level settings"),
"cases with missing covariates is not yet implemented")
expect_warning(
expect_warning(
predict(models$m3b, type = "response")$fitted,
"Prediction in multi-level settings"),
"cases with missing covariates is not yet implemented")
expect_s3_class(predict(models$m3b, type = "lp", warn = FALSE)$fitted,
"data.frame")
expect_s3_class(predict(models$m3b, type = "response", warn = FALSE)$fitted,
"data.frame")
})
test_that("residuals", {
# residuals are not yet implemented
expect_error(residuals(models$m3b, type = "working", warn = FALSE))
expect_error(residuals(models$m3b, type = "response", warn = FALSE))
})
test_that("model can (not) be plottet", {
for (i in seq_along(models)) {
expect_error(plot(models[[i]]))
}
})
test_that("wrong models give errors", {
# time-varying covariate
expect_error(survreg_imp(Surv(futime, status != "censored") ~ copper + sex +
albumin + (1 | id) + (1 | center), timevar = "day",
data = PBC, n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE))
# more than two event types
expect_error(survreg_imp(Surv(futime, status) ~ copper + sex,
data = PBC2, n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE))
# missing values in event time
expect_error(survreg_imp(Surv(futime2, status != "censored") ~ copper + sex,
data = PBC2, n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE))
# missing values in event status
expect_error(survreg_imp(Surv(futime, status2 != "censored") ~ copper + sex,
data = PBC2, n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE))
# wrong outcome
expect_error(survreg_imp(futime ~ copper + sex,
data = PBC2, n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE))
# no argument formula
expect_error(survreg_imp(fixed = futime ~ copper + sex,
data = PBC2, n.adapt = 5, n.iter = 10, seed = 2020,
warn = FALSE, mess = FALSE))
})
# Sys.setenv(IS_CHECK = "")
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