declare_assignment: Declare Data Strategy: Assignment

declare_assignmentR Documentation

Declare Data Strategy: Assignment

Description

Declare Data Strategy: Assignment

Usage

declare_assignment(..., handler = assignment_handler, label = NULL)

assignment_handler(data, ..., legacy = FALSE)

Arguments

...

arguments to be captured, and later passed to the handler

handler

a tidy-in, tidy-out function

label

a string describing the step

data

A data.frame.

legacy

Use the legacy randomizr functionality. This will be disabled in future; please use legacy = FALSE.

Value

A function that takes a data.frame as an argument and returns a data.frame with assignment columns appended.

Examples

# declare_assignment in use
## Two-arm randomized experiment
design <-
  declare_model(
    N = 500,
    X = rep(c(0, 1), each = N / 2),
    U = rnorm(N, sd = 0.25),
    potential_outcomes(Y ~ 0.2 * Z + X + U)
  ) +
  declare_inquiry(ATE = mean(Y_Z_1 - Y_Z_0)) +
  declare_sampling(S = complete_rs(N = N, n = 200)) +
  declare_assignment(Z = complete_ra(N = N, m = 100)) +
  declare_measurement(Y = reveal_outcomes(Y ~ Z)) +
  declare_estimator(Y ~ Z, inquiry = "ATE")

# Set up population to assign
model <- declare_model(
  villages = add_level(
    N = 30, 
    N_households = sample(c(50:100), N, replace = TRUE)
  ),
  households = add_level(
    N = N_households, 
    N_members = sample(c(1, 2, 3, 4), N, 
                       prob = c(0.2, 0.3, 0.25, 0.25), replace = TRUE)
  ),
  individuals = add_level(
    N = N_members, 
    age = sample(18:90, N, replace = TRUE),
    gender = rbinom(n = N, size = 1, prob = .5)
  )
)

# Assignment procedures
## Complete random assignment
design <-
  model +
  declare_assignment(Z = complete_ra(N = N, m = 1000))

## Cluster random assignment
design <-
  model +
  declare_assignment(Z = cluster_ra(clusters = villages,
                                    n = 15))

## Block and cluster random assignment
design <-
  model +
  declare_assignment(Z  = block_and_cluster_ra(
    blocks = villages,
    clusters = households,
    block_m = rep(20, 30)
  ))

## Block random assignment
design <-
  model +
  declare_assignment(Z = block_ra(blocks = gender, m = 100))

## Block random assignment using probabilities
design <-
  model +
  declare_assignment(Z = block_ra(blocks = gender,
                                  block_prob = c(1 / 3, 2 / 3)))

## Factorial assignment
design <-
  model +
  declare_assignment(Z1 = complete_ra(N = N, m = 100),
                     Z2 = block_ra(blocks = Z1))

## Assignment using functions outside of randomizr
design <-
  model +
  declare_assignment(Z = rbinom(n = N, size = 1, prob = 0.35))



DeclareDesign documentation built on June 21, 2022, 1:05 a.m.