library(rprev) context('Diagnostics') data(prevsim) test_that("test_dispersion correct values", { set.seed(17) raw_inc <- c(50, 48, 42, 62, 61, 55) expect_equal(test_dispersion(raw_inc, N_sim = 20), c(0.25, 0.75)) }) test_that("test_dispersion returns doubles", { expect_double <- function(data, N_sim) { expect_match(typeof(test_dispersion(c(30, 25, 28, 40, 62), N_sim = 10)), 'double') } expect_double(incidence(prevsim$entrydate), N_sim = 10) }) test_that("test_dispersion returns no NAs", { expect_NA <- function(data, N_sim) { expect_equal(any(is.na(test_dispersion(c(30, 25, 28, 42, 60), N_sim = 10))), FALSE) } expect_NA(incidence(prevsim$entrydate), N_sim = 10) }) test_that("test_dispersion returns the correct number of values", { expect_length <- function(data, N_sim) { expect_equal(length(test_dispersion(c(50, 42, 55, 60, 30), N_sim = 10)),2) } expect_length(test_dispersion(incidence(prevsim$entrydate), N_sim = 10)) }) test_that("test_prevalence_fit returns same values as before without error and isn't significant", { suppressWarnings(RNGversion("3.5.0")) set.seed(17) prevalence_object <- prevalence("2013-01-01", num_years_to_estimate=10, data=prevsim, inc_formula=entrydate ~ sex, surv_formula=Surv(time, status) ~ sex + age, dist='weibull', death_column='eventdate', N_boot=20) fn <- 'cache/diagnostics/prev_pval.rds' expect_equal_to_reference(test_prevalence_fit(prevalence_object), file=fn) expect_gt(prevalence_object$pval, 0.05) expect_match(typeof(test_prevalence_fit(prevalence_object)), 'double') expect_equal(any(is.na(test_prevalence_fit(prevalence_object))), FALSE) })