tests/testthat/test-experiments-over-networks.R

In rdddr: Companion Datasets and Functions for Blair, Coppock, and Humphreys (2022) "Research Design: Declare, Diagnose, Redesign"

test_that("interference helpers work", {

  skip_if_not_installed("spdep")
  skip_if_not_installed("interference") # https://github.com/szonszein/interference
  skip_on_cran()
  skip("Skipped because interference not yet available on CRAN")

  library(dplyr)
  library(DeclareDesign)
  library(spdep)
  library(interference)

  # Here we obtain the adjacency matrix
  adj_matrix <-
    fairfax |>
    as("Spatial") |>
    poly2nb(queen = TRUE) |>
    nb2mat(style = "B", zero.policy = TRUE)

  # Here we create a permutation matrix of possible random assignments
  ra_declaration <- declare_ra(N = 238, prob = 0.1)

  permutatation_matrix <-
    ra_declaration |>
    obtain_permutation_matrix(maximum_permutations = 10000) |>
    t()

  declaration_18.13 <-
    declare_model(
      data = select(as_tibble(fairfax), -geometry),
      Y_0_0 = pnorm(scale(SHAPE_LEN), sd = 3),
      Y_1_0 = Y_0_0 + 0.02,
      Y_0_1 = Y_0_0 + 0.01,
      Y_1_1 = Y_0_0 + 0.03
    ) +
    declare_inquiry(
      total_ATE = mean(Y_1_1 - Y_0_0),
      direct_ATE = mean(Y_1_0 - Y_0_0),
      indirect_ATE = mean(Y_0_1 - Y_0_0)
    ) +
    declare_assignment(
      Z = conduct_ra(ra_declaration),
      exposure = get_exposure_AS(make_exposure_map_AS(adj_matrix, Z, hop = 1))
    ) +
    declare_measurement(
      Y = case_when(
        exposure == "dir_ind1" ~ Y_1_1,
        exposure == "isol_dir" ~ Y_1_0,
        exposure == "ind1" ~ Y_0_1,
        exposure == "no" ~ Y_0_0
      )
    ) +
    declare_estimator(handler = estimator_AS_tidy,
                      permutatation_matrix = permutatation_matrix,
                      adj_matrix = adj_matrix)

  expect_error(simulate_design(declaration_18.13, sims = 1), NA)

})