context("uncertainty")
#Note tests with use.uncertainty=FALSE are included elsewhere
getSimFit <- function(equal.dispersion){
sim <- SimulateComplete(study.time=365,
number.subjects=100,
event.rates=c(0.01,0.005),
dispersions=0.25)
Simfit(SimulateDropout(sim,drop.mechanism=ConstantRateDrop(rate=0.0025,var=1)),
equal.dispersion=equal.dispersion)
}
test_that("apply.func",{
ans <- apply.func(list(1,2,3),function(x,y)x*y,num.reps=3,y=2)
expect_equal(ans,c(2,4,6,2,4,6,2,4,6))
ans <- apply.func(list(2,5,3),function(x,y)x*y,num.reps=4,y=6)
expect_equal(ans,c(12,30,18,12,30,18,12,30,18,12,30,18))
})
test_that("equal_disp_same_gamma",{
set.seed(33143)
sf <- getSimFit(TRUE)
x1 <- sf$genCoeff.function(TRUE)
expect_equal(x1$gamma[1],x1$gamma[2])
})
test_that("not_equal_disp_diff_gamma",{
set.seed(33143)
sf <- getSimFit(FALSE)
x1 <- sf$genCoeff.function(TRUE)
expect_false(x1$gamma[1]==x1$gamma[2])
})
test_that("same_mu_per_subjects",{
set.seed(33143)
sf <- getSimFit(TRUE)
x1 <- sf$genCoeff.function(TRUE)
expect_true(all(x1$mu[,1]==x1$mu[1,1]))
expect_true(all(x1$mu[,2]==x1$mu[1,2]))
})
test_that("is_stochastic",{
set.seed(33143)
sf <- getSimFit(TRUE)
x1 <- sf$genCoeff.function(TRUE)
x2 <- sf$genCoeff.function(TRUE)
expect_true(all(x1$gamma != x2$gamma))
expect_false(x1$mu[1,1]==x2$mu[1,1])
})
test_that("takes_into_account_uncertainty",{
set.seed(33143)
sf <- getSimFit(TRUE)
x1 <- sf$genCoeff.function(TRUE)
expect_warning(x2 <- sf$genCoeff.function(FALSE))
expect_true(all(x1$gamma != x2$gamma))
expect_false(x1$mu[1,1]==x2$mu[1,1])
})
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