Nothing
library(survivALL)
context("P-value calculations")
###################
#Make example data#
###################
library(survsim)
#Default survival data simulation taken from survsim package reference manual
set.seed(123); sim_dfr <- simple.surv.sim(n=200, foltime=3600,
dist.ev=c("llogistic" ),
anc.ev=c(0.69978200185280),
beta0.ev=c(5.84298525742252),
anc.cens=1.17783687569519,
beta0.cens=7.39773677281100,
z=list(c("unif", 0.8, 1.2)),
beta=list(c(-0.4), c(0)),
x=list(c("bern", 0.5), c("unif", 0.7, 1.3)))
srv <- sim_dfr[c(1, 2, 4)]
measure <- sample(nrow(srv))
#Calculate p-values
test_p <- allPvals(measure, srv, event = "status", time = "stop")
#Because a terminal NA is added so that the length of allPvals() is equall to the length of measure, for some tests we remove this
capless_p <- test_p[-length(test_p)]
###################
#Test example data#
###################
test_that("Ps are numeric", {
expect_true(is.numeric(test_p))
})
test_that("Ps are between 0 and 1", {
expect_true(all(capless_p >= 0))
expect_true(all(capless_p <= 1))
})
test_that("There is 1 P per sample", {
expect_identical(length(test_p), length(measure))
})
test_that("log-rank is identical between survivALL and survdiff calculations", {
})
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.