Reveal Observed Outcomes

reveal_outcomes(data = NULL, outcome_variable_names = Y,
assignment_variable_names = Z, attrition_variable_name = NULL,
outcome_function = NULL)

## Arguments

data A data.frame containing columns of potential outcomes and an assignment variable The outcome prefix(es) of the potential outcomes The bare (unquote) name(s) of the assignment variable The bare (unquote) name of the attrition variable If specified, reveal_outcomes draws outcomes using outcome_function rather than the switching equation.

## Details

Typically, a design includes a potential outcomes declaration and an assignment declaration. Reveal outcomes uses the random assignment to pluck out the correct potential outcomes. This is analogous to the "switching equation" (Gerber and Green 2012, Chapter 2).

## Examples


my_population <- declare_population(N = 100, noise = rnorm(N))

my_potential_outcomes <- declare_potential_outcomes(
Y_Z_0 = noise, Y_Z_1 = noise +
rnorm(N, mean = 2, sd = 2))

my_assignment <- declare_assignment(m = 50)

design <- declare_design(my_population,
my_potential_outcomes,
my_assignment,
reveal_outcomes)

design#>
#> Design Summary
#>
#> Step 1 (population): my_population ---------------------------------------------
#>
#> N = 100
#>
#> Added variable: ID
#>  N_missing N_unique
#>          0      100
#>
#> Added variable: noise
#>    min median mean  max   sd N_missing N_unique
#>  -3.36   0.07 0.00 3.36 1.11         0      100
#>
#> Step 2 (potential outcomes): my_potential_outcomes -----------------------------
#>
#> Added variable: Y_Z_0
#>    min median mean  max   sd N_missing N_unique
#>  -3.36   0.07 0.00 3.36 1.11         0      100
#>
#> Added variable: Y_Z_1
#>    min median mean  max   sd N_missing N_unique
#>  -3.37   1.67 1.81 7.17 2.32         0      100
#>
#> Step 3 (assignment): my_assignment ---------------------------------------------
#>
#> Added variable: Z
#>                0    1
#>   Frequency   50   50
#>  Proportion 0.50 0.50
#>
#> Added variable: Z_cond_prob
#>              0.5
#>   Frequency  100
#>  Proportion 1.00
#>
#> Step 4 (reveal outcomes): reveal_outcomes --------------------------------------
#>
#> Added variable: Y
#>    min median mean  max   sd N_missing N_unique
#>  -3.37   0.45 0.97 7.17 2.02         0      100
#>