`redesign`

quickly generates a design from an existing one by resetting symbols used in design handler parameters in a step's environment (Advanced).

## Arguments

- design
An object of class design.

- ...
Arguments to redesign e.g.,

`n = 100.`

If redesigning multiple arguments, they must be specified as a named list.- expand
If TRUE, redesign using the crossproduct of

`...`

, otherwise recycle them.

## Details

Warning: `redesign`

will edit any symbol in your design, but if the symbol you attempt to change does not exist in a step's environment no changes will be made and no error or warning will be issued.

Please note that `redesign`

functionality is experimental and may be changed in future versions.

## Examples

```
# Two-arm randomized experiment
n <- 500
design <-
declare_model(
N = 1000,
gender = rbinom(N, 1, 0.5),
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 = n)) +
declare_assignment(Z = complete_ra(N = N, m = n/2)) +
declare_measurement(Y = reveal_outcomes(Y ~ Z)) +
declare_estimator(Y ~ Z, inquiry = "ATE")
# Use redesign to return a single modified design
modified_design <- redesign(design, n = 200)
# Use redesign to return a series of modified designs
## Sample size is varied while the rest of the design remains
## constant
design_vary_N <- redesign(design, n = c(100, 500, 900))
if (FALSE) {
# redesign can be used in conjunction with diagnose_designs
# to optimize the design for specific diagnosands
diagnose_designs(design_vary_N)
}
# When redesigning with arguments that are vectors,
# use list() in redesign, with each list item
# representing a design you wish to create
prob_each <- c(.1, .5, .4)
population <- declare_model(N = 1000)
assignment <- declare_assignment(
Z = complete_ra(prob_each = prob_each),
legacy = FALSE)
design <- population + assignment
## returns two designs
designs_vary_prob_each <- redesign(
design,
prob_each = list(c(.2, .5, .3), c(0, .5, .5)))
# To illustrate what does and does not get edited by redesign,
# consider the following three designs. In the first two, argument
# X is called from the step's environment; in the third it is not.
# Using redesign will alter the role of X in the first two designs
# but not the third one.
X <- 3
f <- function(b, X) b*X
g <- function(b) b*X
design1 <- declare_model(N = 1, A = X) + NULL
design2 <- declare_model(N = 1, A = f(2, X)) + NULL
design3 <- declare_model(N = 1, A = g(2)) + NULL
draw_data(design1)
#> ID A
#> 1 1 3
draw_data(design2)
#> ID A
#> 1 1 6
draw_data(design3)
#> ID A
#> 1 1 6
draw_data(redesign(design1, X=0))
#> ID A
#> 1 1 0
draw_data(redesign(design2, X=0))
#> ID A
#> 1 1 0
draw_data(redesign(design3, X=0))
#> ID A
#> 1 1 6
```