Insert, delete and replace steps in an (already declared) design object.
insert_step(design, new_step, before, after)
delete_step(design, step)
replace_step(design, step, new_step)Arguments
- design
A design object, usually created using the + operator,
expand_design, or the design library.- new_step
The new step; Either a function or a partial call.
- before
The step before which to add steps.
- after
The step after which to add steps.
- step
The quoted label of the step to be deleted or replaced.
Value
A new design object.
Details
See modify_design for details.
Examples
my_model <-
declare_model(
N = 100,
U = rnorm(N),
Y_Z_0 = U,
Y_Z_1 = U + rnorm(N, mean = 2, sd = 2)
)
my_assignment <- declare_assignment(Z = complete_ra(N, m = 50))
my_assignment_2 <- declare_assignment(Z = complete_ra(N, m = 25))
design <- my_model + my_assignment
design
#>
#> Design Summary
#>
#> Step 1 (model): declare_model(N = 100, U = rnorm(N), Y_Z_0 = U, Y_Z_1 = U + rnorm(N, mean = 2, sd = 2))
#>
#> N = 100
#>
#> Added variable: ID
#> N_missing N_unique class
#> 0 100 character
#>
#> Added variable: U
#> min median mean max sd N_missing N_unique
#> -2.25 -0.02 0.03 2.39 0.96 0 100
#>
#> Added variable: Y_Z_0
#> min median mean max sd N_missing N_unique
#> -2.25 -0.02 0.03 2.39 0.96 0 100
#>
#> Added variable: Y_Z_1
#> min median mean max sd N_missing N_unique
#> -2.11 2.63 2.49 7.35 1.76 0 100
#>
#> Step 2 (assignment): declare_assignment(Z = complete_ra(N, m = 50)) ------------
#>
#> Added variable: Z
#> 0 1
#> 50 50
#> 0.50 0.50
#>
if (FALSE) {
insert_step(design, declare_step(dplyr::mutate, income = noise^2),
after = my_assignment)
insert_step(design, declare_step(dplyr::mutate, income = noise^2),
before = my_assignment)
# If you are using a design created by a designer, for example from
# the DesignLibrary package, you will not have access to the step
# objects. Instead, you can always use the label of the step.
# get the labels for the steps
names(design)
insert_step(design,
declare_sampling(S = complete_rs(N, n = 50),
legacy = FALSE),
after = "my_pop")
}
delete_step(design, my_assignment)
#>
#> Design Summary
#>
#> Step 1 (model): declare_model(N = 100, U = rnorm(N), Y_Z_0 = U, Y_Z_1 = U + rnorm(N, mean = 2, sd = 2))
#>
#> N = 100
#>
#> Added variable: ID
#> N_missing N_unique class
#> 0 100 character
#>
#> Added variable: U
#> min median mean max sd N_missing N_unique
#> -3.03 0.09 -0.01 2.53 1.02 0 100
#>
#> Added variable: Y_Z_0
#> min median mean max sd N_missing N_unique
#> -3.03 0.09 -0.01 2.53 1.02 0 100
#>
#> Added variable: Y_Z_1
#> min median mean max sd N_missing N_unique
#> -2.52 1.56 1.92 7.81 2.14 0 100
#>
replace_step(design, my_assignment, declare_step(dplyr::mutate, words = "income"))
#>
#> Design Summary
#>
#> Step 1 (model): declare_model(N = 100, U = rnorm(N), Y_Z_0 = U, Y_Z_1 = U + rnorm(N, mean = 2, sd = 2))
#>
#> N = 100
#>
#> Added variable: ID
#> N_missing N_unique class
#> 0 100 character
#>
#> Added variable: U
#> min median mean max sd N_missing N_unique
#> -1.91 -0.05 0.04 2.5 0.94 0 100
#>
#> Added variable: Y_Z_0
#> min median mean max sd N_missing N_unique
#> -1.91 -0.05 0.04 2.5 0.94 0 100
#>
#> Added variable: Y_Z_1
#> min median mean max sd N_missing N_unique
#> -3.3 2.33 2.01 7.67 2.44 0 100
#>
#> Step 2 (custom): declare_step(dplyr::mutate, words = "income") -----------------
#>
#> Added variable: words
#> income
#> 100
#> 1.00
#>