set.seed(42)
sim_dat <- sim_confounded_surv(n=200, list(x1=c("rbinom", 1, 0.5),
x2=c("rbinom", 1, 0.5),
x3=c("rbinom", 1, 0.5)),
treatment_betas=c(x1=0.2, x2=0.4, x3=0.4),
outcome_betas=c(x1=1.1, x2=0, x3=1.1),
group_beta=0)
sim_dat$group2 <- factor(sim_dat$group)
## Just check if function throws any errors
test_that("2 treatments, one confounder", {
adj <- adjustedsurv(data=sim_dat,
variable="group2",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars="x1")
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group2))
})
test_that("2 treatments, one confounder, with conf_int", {
adj <- adjustedsurv(data=sim_dat,
variable="group2",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars="x1",
conf_int=TRUE)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group2))
})
test_that("2 treatments, one confounder, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group2",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars="x1",
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group2))
})
test_that("2 treatments, two confounders", {
adj <- adjustedsurv(data=sim_dat,
variable="group2",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars=c("x1", "x3"))
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group2))
})
test_that("2 treatments, two confounders, with conf_int", {
adj <- adjustedsurv(data=sim_dat,
variable="group2",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars=c("x1", "x3"),
conf_int=TRUE)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group2))
})
test_that("2 treatments, two confounders, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group2",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars=c("x1", "x3"),
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group2))
})
## more than two treatments
sim_dat$group[sim_dat$group==1] <- sample(c(1, 2),
size=nrow(sim_dat[sim_dat$group==1, ]),
replace=TRUE)
sim_dat$group <- factor(sim_dat$group)
test_that("> 2 treatments, one confounder", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars="x1")
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, one confounder, with conf_int", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars="x1",
conf_int=TRUE)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, one confounder, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars="x1",
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, two confounders", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars=c("x1", "x3"))
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, two confounders, with conf_int", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars=c("x1", "x3"),
conf_int=TRUE)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, two confounders, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="strat_nieto",
adjust_vars=c("x1", "x3"),
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
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