tests/testthat/test-concurrent.R

In optic: Simulation Tool for Causal Inference Using Longitudinal Data

#------------------------------------------------------------------------------#
# OPTIC R Package Code Repository
# Copyright (C) 2023 by The RAND Corporation
# See README.md for information on usage and licensing
#------------------------------------------------------------------------------#

# Testing an example of the concurrent method.

data(overdoses)
x <- overdoses

# we will define two scenarios for different effect magnitudes for
# the policies using 5, 10, and 15 percent changes in the outcome
linear5 <- 690 / ((sum(x$population) / length(unique(x$year))) / 100000)
linear10 <- 1380 / ((sum(x$population) / length(unique(x$year))) / 100000)
linear15 <- 2070 / ((sum(x$population) / length(unique(x$year))) / 100000)

scenario1 <- c(linear10, linear10)
scenario2 <- c(linear5, linear15)

# Question: Any suggestion for the name of the object: om? optic_model?
# Question: What are constraints that we should set for each of those parameters:

model_1 <- optic_model(
  name="fixedeff_linear",
  type="reg",
  call="lm",
  formula=crude.rate ~ unemploymentrate + as.factor(year) + as.factor(state) + treatment1_level + treatment2_level,
  weights="population",
  se_adjust=c("none", "cluster"))

model_2 <- optic_model(name="autoreg_linear",
                       type="autoreg",
                       call="lm",
                       formula=crude.rate ~ unemploymentrate + as.factor(year) + treatment1_change + treatment2_change,
                       weights= "population",
                       se_adjust=c("none", "cluster"))



test_that("can create optic_model", {
  
  expect_s3_class(model_1, "optic_model")
  
})


# Test Concurrent Methods -------------------------------------------------

concurrent_optic_sim <- optic_simulation(
  x=overdoses,
  models=list(model_1, model_2),
  iters=2,
  method="concurrent",
  unit_var="state",
  time_var="year",
  effect_magnitude=list(scenario1, scenario2),
  n_units=c(10),
  effect_direction=c("neg", "pos"),
  policy_speed=c("instant", "slow"),
  n_implementation_periods=c(3),
  rhos=c(0, 0.5, 0.9),
  years_apart=2,
  ordered=TRUE
)

# cluster_adjust_se <- optic:::cluster_adjust_se

concurrent_results_list <- dispatch_simulations(
  concurrent_optic_sim,
  use_future=T,
  seed=9782,
  verbose=2,
  future.globals=c("cluster_adjust_se"),
  future.packages=c("dplyr", "optic")
)

concurrent_results <- do.call(rbind, concurrent_results_list) %>% as.data.frame()

test_that("concurrent simulations work", {
  
  expect_type(concurrent_results_list, "list")
  
  expect_false(any(is.na(concurrent_results)))
  
})