tests/testthat/test-check_kolmogorov_smirnov.R

In CausalGPS: Matching on Generalized Propensity Scores with Continuous Exposures

test_that("check_kolmogorov_smirnov works as expected.", {
  skip_on_cran()
  data.table::setDTthreads(1)
  set.seed(8422)
  n <- 200
  mydata <- generate_syn_data(sample_size=n)
  year <- sample(x=c("2001","2002","2003","2004","2005"),size = n, replace = TRUE)
  region <- sample(x=c("North", "South", "East", "West"),size = n, replace = TRUE)
  mydata$year <- as.factor(year)
  mydata$region <- as.factor(region)
  mydata$cf5 <- as.factor(mydata$cf5)

  pseudo_pop <- generate_pseudo_pop(mydata[, c("id", "w")],
                                    mydata[, c("id", "cf1", "cf2", "cf3",
                                               "cf4","cf5","cf6",
                                               "year","region")],
                                    ci_appr = "matching",
                                    gps_density = "kernel",
                                    exposure_trim_qtls = c(0.01,0.99),
                                    sl_lib = c("m_xgboost"),
                                    covar_bl_method = "absolute",
                                    covar_bl_trs = 0.1,
                                    covar_bl_trs_type = "mean",
                                    max_attempt = 1,
                                    dist_measure = "l1",
                                    delta_n = 1,
                                    scale = 0.5,
                                    nthread = 1)

  output <- CausalGPS:::check_kolmogorov_smirnov(w = pseudo_pop$pseudo_pop[, c("w")],
                                                 c = pseudo_pop$pseudo_pop[ ,
                                                                            pseudo_pop$covariate_cols_name],
                                                 counter = pseudo_pop$pseudo_pop[, c("counter_weight")],
                                                 ci_appr="matching",
                                                 nthread=1)

  expect_equal(length(output), 2L)
  expect_equal(length(output$ks_stat), 9L)
  expect_equal(length(output$stat_vals), 3L)
  expect_equal(output$ks_stat[["w"]], 0.1098639, tolerance = 0.000001)
  expect_equal(output$ks_stat[["cf3"]], 0.1319728, tolerance = 0.000001)
  expect_equal(output$stat_vals[["maximal_val"]], 0.1931973, tolerance = 0.000001)
})