Nothing
context("Sample size 1")
library(BivRec)
bivrec_data <- simBivRec(nsize=1, beta1=c(0.5,0.5), beta2=c(0,-0.5),
tau_c=63, set=1.1)
test_that("data check 1", {
expect_is(bivrec_data, "data.frame")
expect_equal(unique(bivrec_data$id), 1)
})
check_np <- function() {
if (max(bivrec_data$epi)==1) {
skip("np check")
}
}
check_reg <- function() {
if (max(bivrec_data$epi)==1) {
expect_error(bivrecReg(bivrecSurv(id, epi, xij, yij, d1, d2) ~ a1 + a2,
bivrec_data, "Lee.et.al"))
expect_error(bivrecReg(bivrecSurv(id, epi, xij, yij, d1, d2) ~ a1 + a2,
bivrec_data, "Chang"))
}
}
### Lee and Chang methods for 1 subject with several episodes may work
#### or may lead to singular systems / no convergence
test_that("np check", {
npresult <- bivrecNP(response = with(bivrec_data, bivrecSurv(id, epi, xij, yij, d1, d2)),
ai=1, u1 = seq(2, 15, 1), u2 = seq(1, 10, 1), conditional = FALSE)
expect_is(npresult, "bivrecNP")
expect_is(npresult$joint_cdf, "data.frame")
expect_is(npresult$marginal_survival, "data.frame")
expect_is(npresult$conditional_cdf, "NULL")
#note that conditional SE and CI's are bootstrap based so cannot run conditional for a sample of 1
})
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