test_that("seed works for OLS", { skip_on_cran() skip_if_not( find_proglang("julia"), message = "skip test as julia installation not found." ) set.seed(12312) dqrng::dqset.seed(9786) #' @srrstats {G5.0} *Where applicable or practicable, tests should use #' standard data sets with known properties (for example, the #' [NIST Standard Reference Datasets](https://www.itl.nist.gov/div898/strd/), #' or data sets provided by other widely-used R packages).* All tests are based #' on random data sets. data1 <<- fwildclusterboot:::create_data( N = 5000, N_G1 = 40, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1 ) lm_fit <- lm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, data = data1 ) for (engine in c("R", "R-lean", "WildBootTests.jl")) { # Case 1: seed set, no internal seeds set.seed(123) dqrng::dqset.seed(123) boot_lm_s1 <- suppressMessages( boottest( object = lm_fit, clustid = "group_id1", B = 999, param = "treatment", type = "rademacher", conf_int = FALSE, engine = engine ) ) boot_lm_s2 <- suppressMessages( boottest( object = lm_fit, clustid = "group_id1", B = 999, param = "treatment", type = "rademacher", conf_int = FALSE, engine = engine ) ) expect_true(boot_lm_s1$p_val != boot_lm_s2$p_val) # Case 5: different starting seeds set.seed(9) dqrng::dqset.seed(9) boot_lm_s1 <- suppressMessages( boottest( object = lm_fit, clustid = "group_id1", B = 999, param = "treatment", type = "rademacher", conf_int = FALSE, engine = engine ) ) set.seed(2) dqrng::dqset.seed(2) boot_lm_s2 <- suppressMessages( boottest( object = lm_fit, clustid = "group_id1", B = 999, param = "treatment", type = "rademacher", conf_int = FALSE, engine = engine ) ) expect_true(boot_lm_s1$p_val != boot_lm_s2$p_val) } })