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Reveal observed outcomes from potential outcomes columns

Source: R/potential_outcomes.R
reveal_outcomes.Rd

Implements the switching equation: for each unit, selects the potential outcome column corresponding to that unit's realized assignment.

Usage

reveal_outcomes(x, sep = "_")

Arguments

x

A formula of the form outcome ~ assignment or outcome ~ Z1 + Z2 for factorial assignments. The outcome name and assignment variable(s) must match columns already in the data (typically created by potential_outcomes).

sep

Column-name separator. Default "_". It must match the sep given to potential_outcomes().

Value

A vector with one element per row, holding each unit's outcome under the assignment it actually received, and carrying the type of the potential outcome columns it reads. A factor reveals as a factor, keeping its levels and their order, and a Date as a Date. Where the conditions do not agree on one set of factor levels there are none to keep, so the result is character and a warning says so.

Examples

dat <- fabricate(
  N = 10, U = rnorm(N),
  potential_outcomes(Y ~ 0.5 * Z + U)
)
fabricate(
  data = dat,
  Z = rbinom(N, 1, 0.5),
  Y = reveal_outcomes(Y ~ Z)
)
#> # A tibble: 10 × 6
#>    ID          U   Y_Z_0  Y_Z_1     Z       Y
#>    <chr>   <dbl>   <dbl>  <dbl> <int>   <dbl>
#>  1 01     0.143   0.143   0.643     1  0.643 
#>  2 02     1.02    1.02    1.52      0  1.02  
#>  3 03    -2.40   -2.40   -1.90      1 -1.90  
#>  4 04     0.218   0.218   0.718     0  0.218 
#>  5 05    -0.396  -0.396   0.104     0 -0.396 
#>  6 06     3.13    3.13    3.63      1  3.63  
#>  7 07    -0.0268 -0.0268  0.473     0 -0.0268
#>  8 08    -0.753  -0.753  -0.253     1 -0.253 
#>  9 09     0.0182  0.0182  0.518     1  0.518 
#> 10 10    -0.742  -0.742  -0.242     0 -0.742 

# A separator other than "_" is given to both
fabricate(
  N = 10, U = rnorm(N),
  potential_outcomes(Y ~ 0.5 * Z + U, sep = "."),
  Z = rbinom(N, 1, 0.5),
  Y = reveal_outcomes(Y ~ Z, sep = ".")
)
#> # A tibble: 10 × 6
#>    ID         U  Y.Z.0  Y.Z.1     Z      Y
#>    <chr>  <dbl>  <dbl>  <dbl> <int>  <dbl>
#>  1 01    -0.220 -0.220  0.280     0 -0.220
#>  2 02    -0.774 -0.774 -0.274     0 -0.774
#>  3 03     2.32   2.32   2.82      0  2.32 
#>  4 04     1.53   1.53   2.03      1  2.03 
#>  5 05     0.635  0.635  1.13      1  1.13 
#>  6 06    -0.149 -0.149  0.351     0 -0.149
#>  7 07    -0.240 -0.240  0.260     0 -0.240
#>  8 08    -1.51  -1.51  -1.01      0 -1.51 
#>  9 09     1.02   1.02   1.52      1  1.52 
#> 10 10    -1.04  -1.04  -0.541     0 -1.04