tests/testthat/test_surv_direct.r
In RobinDenz1/adjustedCurves: Confounder-Adjusted Survival Curves and Cumulative Incidence Functions
library(survival)
set.seed(42)
sim_dat <- readRDS(system.file("testdata",
"d_sim_surv_n_50.Rds",
package="adjustedCurves"))
sim_dat$group <- as.factor(sim_dat$group)
# outcome model
mod <- survival::coxph(Surv(time, event) ~ x1 + x2 + x3 + x4 + x5 + x6 + group,
data=sim_dat, x=TRUE)
## Just check if function throws any errors
test_that("2 treatments, no conf_int, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("2 treatments, with conf_int, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("2 treatments, no conf_int, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("2 treatments, with conf_int, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("2 treatments, no conf_int, no boot, with times", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod,
times=c(0.8, 0.9))
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
sim_dat <- readRDS(system.file("testdata",
"d_sim_surv_n_100.Rds",
package="adjustedCurves"))
sim_dat$group[sim_dat$group==1] <- sample(c(1, 2),
size=nrow(sim_dat[sim_dat$group==1, ]),
replace=TRUE)
sim_dat$group <- as.factor(sim_dat$group)
# outcome model
mod <- survival::coxph(Surv(time, event) ~ x1 + x2 + x3 + x4 + x5 + group,
data=sim_dat, x=T)
test_that("> 2 treatments, no conf_int, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, with conf_int, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, no conf_int, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, with conf_int, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, no conf_int, no boot, with times", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
bootstrap=FALSE,
n_boot=2,
outcome_model=mod,
times=c(0.8, 0.9))
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
####################### Models other than coxph ################################
library(prodlim)
set.seed(41)
sim_dat <- readRDS(system.file("testdata",
"d_sim_surv_n_150.Rds",
package="adjustedCurves"))
sim_dat$group <- as.factor(sim_dat$group)
# fit some models
mod_riskRegression <- riskRegression::riskRegression(Hist(time, event) ~
group + x1,
data=sim_dat, cause=1)
mod_ARR <- riskRegression::ARR(Hist(time, event) ~ group + x1 + x6,
data=sim_dat, cause=1)
mod_selectCox <- pec::selectCox(survival::Surv(time, event) ~ group + x1,
data=sim_dat)
mod_pecRpart <- pec::pecRpart(survival::Surv(time, event) ~ group + x1,
data=sim_dat)
mod_prodlim <- prodlim::prodlim(Hist(time, event) ~ group + x1,
data=sim_dat)
mod_glm <- stats::glm(time ~ group + x1, data=sim_dat, family="gaussian")
# run tests for each model
test_that("riskRegression, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_riskRegression)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("riskRegression, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_riskRegression,
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$group))
})
test_that("ARR, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_ARR)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("ARR, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_ARR,
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$group))
})
test_that("selectCox, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_selectCox)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("selectCox, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_selectCox,
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$group))
})
test_that("pecRpart, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_pecRpart)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("prodlim, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_prodlim)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("prodlim, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_prodlim,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
sim_dat$event <- 1
test_that("glm, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_glm)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("glm, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_glm,
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$group))
})
### using > 2 treatments
set.seed(42)
sim_dat <- readRDS(system.file("testdata",
"d_sim_surv_n_150.Rds",
package="adjustedCurves"))
sim_dat$group[sim_dat$group==1] <- sample(c(1, 2),
size=nrow(sim_dat[sim_dat$group==1, ]),
replace=TRUE)
sim_dat$group <- as.factor(sim_dat$group)
# fit some models
mod_riskRegression <- riskRegression::riskRegression(Hist(time, event) ~
group + x1,
data=sim_dat, cause=1)
mod_ARR <- riskRegression::ARR(Hist(time, event) ~ group + x1 + x6,
data=sim_dat, cause=1)
mod_selectCox <- pec::selectCox(Surv(time, event) ~ group + x1,
data=sim_dat)
mod_pecRpart <- pec::pecRpart(Surv(time, event) ~ group + x1,
data=sim_dat)
mod_prodlim <- prodlim::prodlim(Hist(time, event) ~ group + x1,
data=sim_dat)
mod_glm <- stats::glm(time ~ group + x1, data=sim_dat, family="gaussian")
# run tests
test_that("riskRegression, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_riskRegression)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("riskRegression, > 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_riskRegression,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("ARR, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_ARR)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("ARR, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_ARR,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("selectCox, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_selectCox)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("selectCox, > 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_selectCox,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("pecRpart, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_pecRpart)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("prodlim, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_prodlim)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("prodlim, > 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_prodlim,
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$group))
})
sim_dat$event <- 1
test_that("glm, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_glm)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("glm, > 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_glm,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
################################################################################
# NOTE: These models are supported, but would require all kinds of package
# dependencies if tested here. The tests are run in the development
# process but are commented out here.
#
#mod_pecCforest <- pec::pecCforest(Surv(time, event) ~ group + x1,
# data=sim_dat,
# control=party::cforest_unbiased(mtry=2))
#library(timereg)
#mod_aalen <- timereg::aalen(Surv(time, event) ~ group + x1,
# data=sim_dat, max.time=7, n.sim=100)
#mod_cox.aalen <- timereg::cox.aalen(Surv(time, event) ~ prop(group) + prop(x1),
# data=sim_dat)
#library(rms)
#mod_psm <- rms::psm(Surv(time, event) ~ group + x1,
# data=sim_dat)
#mod_ols <- rms::ols(time ~ group + x1, data=sim_dat, x=TRUE, y=TRUE)
#library(flexsurv)
#mod_flexsurvreg <- flexsurv::flexsurvreg(Surv(time, event) ~ group + x1,
# data=sim_dat, dist="gengamma")
#library(randomForest)
#mod_randomForest <- randomForest::randomForest(time ~ group + x1, data=sim_dat)
#library(ranger)
#mod_ranger <- ranger::ranger(Surv(time, event) ~ group + x1 + x6, data=sim_dat)
#library(randomForestSRC)
#mod_rfsrc <- randomForestSRC::rfsrc(Surv(time, event) ~ group + x1 + x6,
# data=sim_dat)
#library(penalized)
#mod_penalizedS3 <- riskRegression::penalizedS3(Surv(time, event) ~ group + x1 +
# x6, data=sim_dat,
# lambda1=1, maxiter=1)
#library(gbm)
#mod_gbm <- gbm::gbm(Surv(time, event) ~ group + x1 + x6, data=sim_dat,
# distribution="coxph")
#library(casebase)
#mod_fitSmoothHazard <- casebase::fitSmoothHazard(event ~ time + x1 + group,
# sim_dat, ratio=10)
#
#library(mexhaz)
#mod_mexhaz <- mexhaz::mexhaz(Surv(time, event) ~ group + x1 + x6, data=sim_dat)
#
#test_that("pecCforest, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_pecCforest),
# NA)
#})
#
#test_that("pecCforest, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_pecCforest,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("aalen, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_aalen),
# NA)
#})
#
#test_that("aalen, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_aalen,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
## NOTE: cox.aalen currently doesn't work due to bugs in predictRisk and
## predictSurvProb
#test_that("cox.aalen, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_cox.aalen),
# NA)
#})
#
## NOTE: cox.aalen currently doesn't work due to bugs in predictRisk and
## predictSurvProb
#test_that("cox.aalen, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_cox.aalen,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("psm, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_psm),
# NA)
#})
#
#test_that("psm, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_psm,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("flexsurvreg, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_flexsurvreg),
# NA)
#})
#
#test_that("flexsurvreg, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_flexsurvreg,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("randomForest, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_randomForest),
# NA)
#})
#
#test_that("randomForest, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_randomForest,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("ols, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_ols),
# NA)
#})
#
#test_that("ols, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_ols,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("ranger, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_ranger),
# NA)
#})
#
#test_that("ranger, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_ranger,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("rfsrc, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_rfsrc),
# NA)
#})
#
#test_that("rfsrc, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_rfsrc,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("penalizedS3, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_penalizedS3),
# NA)
#})
#
#test_that("penalizedS3, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_penalizedS3,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("gbm, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_gbm),
# NA)
#})
#
#test_that("gbm, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_gbm,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
## NOTE: Currently doesn't work due to bugs in casebase
#test_that("fitSmoothHazard, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_fitSmoothHazard),
# NA)
#})
#
## NOTE: Currently doesn't work due to bugs in casebase
#test_that("fitSmoothHazard, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_fitSmoothHazard,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("mexhaz, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_mexhaz),
# NA)
#})
#
#test_that("mexhaz, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_mexhaz,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
RobinDenz1/adjustedCurves documentation built on Sept. 27, 2024, 7:04 p.m.
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library(survival)
set.seed(42)
sim_dat <- readRDS(system.file("testdata",
"d_sim_surv_n_50.Rds",
package="adjustedCurves"))
sim_dat$group <- as.factor(sim_dat$group)
# outcome model
mod <- survival::coxph(Surv(time, event) ~ x1 + x2 + x3 + x4 + x5 + x6 + group,
data=sim_dat, x=TRUE)
## Just check if function throws any errors
test_that("2 treatments, no conf_int, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("2 treatments, with conf_int, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("2 treatments, no conf_int, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("2 treatments, with conf_int, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("2 treatments, no conf_int, no boot, with times", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod,
times=c(0.8, 0.9))
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
sim_dat <- readRDS(system.file("testdata",
"d_sim_surv_n_100.Rds",
package="adjustedCurves"))
sim_dat$group[sim_dat$group==1] <- sample(c(1, 2),
size=nrow(sim_dat[sim_dat$group==1, ]),
replace=TRUE)
sim_dat$group <- as.factor(sim_dat$group)
# outcome model
mod <- survival::coxph(Surv(time, event) ~ x1 + x2 + x3 + x4 + x5 + group,
data=sim_dat, x=T)
test_that("> 2 treatments, no conf_int, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, with conf_int, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, no conf_int, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, with conf_int, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=TRUE,
bootstrap=TRUE,
n_boot=2,
outcome_model=mod)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("> 2 treatments, no conf_int, no boot, with times", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
bootstrap=FALSE,
n_boot=2,
outcome_model=mod,
times=c(0.8, 0.9))
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
####################### Models other than coxph ################################
library(prodlim)
set.seed(41)
sim_dat <- readRDS(system.file("testdata",
"d_sim_surv_n_150.Rds",
package="adjustedCurves"))
sim_dat$group <- as.factor(sim_dat$group)
# fit some models
mod_riskRegression <- riskRegression::riskRegression(Hist(time, event) ~
group + x1,
data=sim_dat, cause=1)
mod_ARR <- riskRegression::ARR(Hist(time, event) ~ group + x1 + x6,
data=sim_dat, cause=1)
mod_selectCox <- pec::selectCox(survival::Surv(time, event) ~ group + x1,
data=sim_dat)
mod_pecRpart <- pec::pecRpart(survival::Surv(time, event) ~ group + x1,
data=sim_dat)
mod_prodlim <- prodlim::prodlim(Hist(time, event) ~ group + x1,
data=sim_dat)
mod_glm <- stats::glm(time ~ group + x1, data=sim_dat, family="gaussian")
# run tests for each model
test_that("riskRegression, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_riskRegression)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("riskRegression, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_riskRegression,
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$group))
})
test_that("ARR, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_ARR)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("ARR, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_ARR,
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$group))
})
test_that("selectCox, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_selectCox)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("selectCox, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_selectCox,
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$group))
})
test_that("pecRpart, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_pecRpart)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("prodlim, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_prodlim)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("prodlim, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_prodlim,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
sim_dat$event <- 1
test_that("glm, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_glm)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("glm, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_glm,
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$group))
})
### using > 2 treatments
set.seed(42)
sim_dat <- readRDS(system.file("testdata",
"d_sim_surv_n_150.Rds",
package="adjustedCurves"))
sim_dat$group[sim_dat$group==1] <- sample(c(1, 2),
size=nrow(sim_dat[sim_dat$group==1, ]),
replace=TRUE)
sim_dat$group <- as.factor(sim_dat$group)
# fit some models
mod_riskRegression <- riskRegression::riskRegression(Hist(time, event) ~
group + x1,
data=sim_dat, cause=1)
mod_ARR <- riskRegression::ARR(Hist(time, event) ~ group + x1 + x6,
data=sim_dat, cause=1)
mod_selectCox <- pec::selectCox(Surv(time, event) ~ group + x1,
data=sim_dat)
mod_pecRpart <- pec::pecRpart(Surv(time, event) ~ group + x1,
data=sim_dat)
mod_prodlim <- prodlim::prodlim(Hist(time, event) ~ group + x1,
data=sim_dat)
mod_glm <- stats::glm(time ~ group + x1, data=sim_dat, family="gaussian")
# run tests
test_that("riskRegression, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_riskRegression)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("riskRegression, > 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_riskRegression,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("ARR, 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_ARR)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("ARR, 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_ARR,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("selectCox, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_selectCox)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("selectCox, > 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_selectCox,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("pecRpart, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_pecRpart)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("prodlim, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_prodlim)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("prodlim, > 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_prodlim,
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$group))
})
sim_dat$event <- 1
test_that("glm, > 2 treatments, no boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_glm)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
test_that("glm, > 2 treatments, with boot", {
adj <- adjustedsurv(data=sim_dat,
variable="group",
ev_time="time",
event="event",
method="direct",
conf_int=FALSE,
outcome_model=mod_glm,
bootstrap=TRUE,
n_boot=2)
expect_s3_class(adj, "adjustedsurv")
expect_true(is.numeric(adj$adj$surv))
expect_equal(levels(adj$adj$group), levels(sim_dat$group))
})
################################################################################
# NOTE: These models are supported, but would require all kinds of package
# dependencies if tested here. The tests are run in the development
# process but are commented out here.
#
#mod_pecCforest <- pec::pecCforest(Surv(time, event) ~ group + x1,
# data=sim_dat,
# control=party::cforest_unbiased(mtry=2))
#library(timereg)
#mod_aalen <- timereg::aalen(Surv(time, event) ~ group + x1,
# data=sim_dat, max.time=7, n.sim=100)
#mod_cox.aalen <- timereg::cox.aalen(Surv(time, event) ~ prop(group) + prop(x1),
# data=sim_dat)
#library(rms)
#mod_psm <- rms::psm(Surv(time, event) ~ group + x1,
# data=sim_dat)
#mod_ols <- rms::ols(time ~ group + x1, data=sim_dat, x=TRUE, y=TRUE)
#library(flexsurv)
#mod_flexsurvreg <- flexsurv::flexsurvreg(Surv(time, event) ~ group + x1,
# data=sim_dat, dist="gengamma")
#library(randomForest)
#mod_randomForest <- randomForest::randomForest(time ~ group + x1, data=sim_dat)
#library(ranger)
#mod_ranger <- ranger::ranger(Surv(time, event) ~ group + x1 + x6, data=sim_dat)
#library(randomForestSRC)
#mod_rfsrc <- randomForestSRC::rfsrc(Surv(time, event) ~ group + x1 + x6,
# data=sim_dat)
#library(penalized)
#mod_penalizedS3 <- riskRegression::penalizedS3(Surv(time, event) ~ group + x1 +
# x6, data=sim_dat,
# lambda1=1, maxiter=1)
#library(gbm)
#mod_gbm <- gbm::gbm(Surv(time, event) ~ group + x1 + x6, data=sim_dat,
# distribution="coxph")
#library(casebase)
#mod_fitSmoothHazard <- casebase::fitSmoothHazard(event ~ time + x1 + group,
# sim_dat, ratio=10)
#
#library(mexhaz)
#mod_mexhaz <- mexhaz::mexhaz(Surv(time, event) ~ group + x1 + x6, data=sim_dat)
#
#test_that("pecCforest, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_pecCforest),
# NA)
#})
#
#test_that("pecCforest, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_pecCforest,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("aalen, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_aalen),
# NA)
#})
#
#test_that("aalen, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_aalen,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
## NOTE: cox.aalen currently doesn't work due to bugs in predictRisk and
## predictSurvProb
#test_that("cox.aalen, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_cox.aalen),
# NA)
#})
#
## NOTE: cox.aalen currently doesn't work due to bugs in predictRisk and
## predictSurvProb
#test_that("cox.aalen, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_cox.aalen,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("psm, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_psm),
# NA)
#})
#
#test_that("psm, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_psm,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("flexsurvreg, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_flexsurvreg),
# NA)
#})
#
#test_that("flexsurvreg, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_flexsurvreg,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("randomForest, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_randomForest),
# NA)
#})
#
#test_that("randomForest, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_randomForest,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("ols, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_ols),
# NA)
#})
#
#test_that("ols, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_ols,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("ranger, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_ranger),
# NA)
#})
#
#test_that("ranger, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_ranger,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("rfsrc, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_rfsrc),
# NA)
#})
#
#test_that("rfsrc, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_rfsrc,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("penalizedS3, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_penalizedS3),
# NA)
#})
#
#test_that("penalizedS3, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_penalizedS3,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("gbm, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_gbm),
# NA)
#})
#
#test_that("gbm, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_gbm,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
## NOTE: Currently doesn't work due to bugs in casebase
#test_that("fitSmoothHazard, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_fitSmoothHazard),
# NA)
#})
#
## NOTE: Currently doesn't work due to bugs in casebase
#test_that("fitSmoothHazard, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_fitSmoothHazard,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
#
#test_that("mexhaz, 2 treatments, no boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_mexhaz),
# NA)
#})
#
#test_that("mexhaz, 2 treatments, with boot", {
# expect_error(adjustedCurves::adjustedsurv(data=sim_dat,
# variable="group",
# ev_time="time",
# event="event",
# method="direct",
# conf_int=FALSE,
# outcome_model=mod_mexhaz,
# bootstrap=TRUE,
# n_boot=2),
# NA)
#})
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