regression_discontinuity_designer {DesignLibrary} | R Documentation |
Builds a design with sample from population of size N
. The average treatment effect local to the cutpoint is equal to tau
. It allows for specification of the order of the polynomial regression (poly_reg_order
), cutoff value on the running variable (cutoff
), and size of bandwidth around the cutoff (bandwidth
). By providing a vector of numbers to control_coefs
and treatment_coefs
, users can also specify polynomial regression coefficients that generate the expected control and treatment potential outcomes given the running variable.
regression_discontinuity_designer(
N = 1000,
tau = 0.15,
outcome_sd = 0.1,
cutoff = 0.5,
bandwidth = 0.5,
control_coefs = c(0.5, 0.5),
treatment_coefs = c(-5, 1),
poly_reg_order = 4,
args_to_fix = NULL
)
N |
An integer. Size of population to sample from. |
tau |
A number. Difference in potential outcomes functions at the threshold. |
outcome_sd |
A positive number. The standard deviation of the outcome. |
cutoff |
A number in (0,1). Threshold on running variable beyond which units are treated. |
bandwidth |
A number. The value of the bandwidth on both sides of the threshold from which to include units. |
control_coefs |
A vector of numbers. Coefficients for polynomial regression function that generates control potential outcomes. Order of polynomial is equal to length. |
treatment_coefs |
A vector of numbers. Coefficients for polynomial regression function that generates treatment potential outcomes. Order of polynomial is equal to length. |
poly_reg_order |
Integer greater than or equal to 1. Order of the polynomial regression used to estimate the jump at the cutoff. |
args_to_fix |
A character vector. Names of arguments to be args_to_fix in design. |
See vignette online.
A regression discontinuity design.
# Generate a regression discontinuity design using default arguments:
regression_discontinuity_design <- regression_discontinuity_designer()