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  1. library(DeclareDesign)
  2. proportion_shy <- .06
  3.  
  4. population <- declare_population(
  5.   N = 5000,
  6.   # true trump vote (unobservable)
  7.   truthful_trump_vote = draw_binary(.45, N),
  8.  
  9.   # shy voter (unobservable)  
  10.   shy = draw_binary(proportion_shy, N),
  11.  
  12.   # Direct question response (1 if Trump supporter and not shy, 0 otherwise)
  13.   Y_direct = as.numeric(truthful_trump_vote == 1 & shy == 0),
  14.  
  15.   # Nonsensitive list experiment items
  16.   raise_minimum_wage = draw_binary(.8, N),
  17.   repeal_obamacare = draw_binary(.6, N),
  18.   ban_assault_weapons = draw_binary(.5, N)
  19. )
  20.  
  21. potential_outcomes <- declare_potential_outcomes(
  22.   Y_list_Z_0 = raise_minimum_wage + repeal_obamacare + ban_assault_weapons,
  23.   Y_list_Z_1 = Y_list_Z_0 + truthful_trump_vote
  24. )
  25.  
  26. # Inquiry -----------------------------------------------------------------
  27. estimand <- declare_estimand(
  28.   proportion_truthful_trump_vote = mean(truthful_trump_vote))
  29.  
  30. # Data Strategy -----------------------------------------------------------
  31. sampling <- declare_sampling(n = 500)
  32. assignment <- declare_assignment(prob = .5)
  33.  
  34. # Answer Strategy ---------------------------------------------------------
  35. estimator_direct <- declare_estimator(
  36.   Y_direct ~ 1,
  37.   model = lm_robust,
  38.   term = "(Intercept)",
  39.   estimand = estimand,
  40.   label = "direct"
  41. )
  42.  
  43. estimator_list <- declare_estimator(Y_list ~ Z,
  44.                                     model = difference_in_means,
  45.                                     estimand = estimand,
  46.                                     label = "list")
  47.  
  48. # Design ------------------------------------------------------------------
  49. design <-
  50.   population +
  51.   potential_outcomes +
  52.   sampling +
  53.   estimand +
  54.   assignment +
  55.   declare_reveal(outcome_variables = Y_list) +
  56.   estimator_direct +
  57.   estimator_list
  58.  
  59. draw_data(design)
  60.  
  61. diagnosis <- diagnose_design(design, sims = 500, bootstrap_sims = FALSE)
  62. diagnosis
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