library(survival) library(tidyverse) files <- Sys.glob("~/Documents/GitHub/RobinCar/R/*.R") map(files, source) DATA <- ovarian %>% rename(tte = futime, obs = fustat) %>% arrange(tte) test_that("Logrank influence function error checking 6", { DATA$id <- DATA$ecog.ps expect_error(robincar_logrank( adj_method = "CL", df = DATA, treat_col = "rx", p_trt = 0.5, ref_arm = 1, response_col = "tte", event_col = "obs", return_influence = T, id_col = "idx" ), "Column idx not found") }) test_that("Logrank influence function error checking 5", { DATA$id <- DATA$ecog.ps expect_no_error(robincar_logrank( adj_method = "CL", df = DATA, treat_col = "rx", p_trt = 0.5, covariate_col = "id", ref_arm = 1, response_col = "tte", event_col = "obs" )) }) test_that("Logrank influence function error checking 4", { DATA$idx <- 1:nrow(DATA) DATA$id <- DATA$ecog.ps expect_error(robincar_logrank( adj_method = "CL", df = DATA, treat_col = "rx", p_trt = 0.5, covariate_col = "id", ref_arm = 1, response_col = "tte", event_col = "obs", return_influence = T, id_col = "idx" ), "if return_influence is TRUE, no covariate can be called 'id'.") }) test_that("Logrank influence function error checking 3", { DATA$idx <- 1:nrow(DATA) expect_error(robincar_logrank( adj_method = "CL", df = DATA, treat_col = "rx", p_trt = 0.5, ref_arm = 1, response_col = "tte", event_col = "obs", return_influence = "cheese", id_col = "idx" ), "return_influence must be either TRUE or FALSE") }) test_that("Logrank influence function error checking 2", { DATA$idx <- 5 expect_error(robincar_logrank( adj_method = "CL", df = DATA, treat_col = "rx", p_trt = 0.5, ref_arm = 1, response_col = "tte", event_col = "obs", return_influence = T, id_col = "idx" ), "Id column must not have duplicated values") }) test_that("Logrank influence function error checking 1", { expect_error(robincar_logrank( adj_method = "CL", df = DATA, treat_col = "rx", p_trt = 0.5, ref_arm = 1, response_col = "tte", event_col = "obs", return_influence = T ), "id_col must not be NULL if return_influence is TRUE") }) test_that("Logrank influence function", { DATA$idx <- 1:nrow(DATA) RC1 <- robincar_logrank( adj_method = "CL", df = DATA, treat_col = "rx", p_trt = 0.5, ref_arm = 1, response_col = "tte", event_col = "obs", return_influence = T, id_col = "idx" ) expect_equal(sum(RC1$result$inf_func$inf_func), RC1$result$strata_sum$U_SL_z[1]) })